|
{ |
|
"ctfidf_model": { |
|
"bm25_weighting": false, |
|
"reduce_frequent_words": false |
|
}, |
|
"vectorizer_model": { |
|
"params": { |
|
"analyzer": "word", |
|
"binary": false, |
|
"decode_error": "strict", |
|
"encoding": "utf-8", |
|
"input": "content", |
|
"lowercase": true, |
|
"max_df": 1.0, |
|
"max_features": null, |
|
"min_df": 2, |
|
"ngram_range": [ |
|
1, |
|
5 |
|
], |
|
"stop_words": "english", |
|
"strip_accents": null, |
|
"token_pattern": "(?u)\\b\\w\\w+\\b", |
|
"vocabulary": null |
|
}, |
|
"vocab": { |
|
"improving": 2805, |
|
"relation": 5310, |
|
"extraction": 2105, |
|
"pretrained": 4835, |
|
"language": 3137, |
|
"representations": 5363, |
|
"current": 1268, |
|
"stateoftheart": 5906, |
|
"methods": 3751, |
|
"typically": 6515, |
|
"rely": 5329, |
|
"set": 5668, |
|
"lexical": 3441, |
|
"syntactic": 6094, |
|
"semantic": 5619, |
|
"features": 2164, |
|
"explicitly": 2061, |
|
"computed": 1054, |
|
"preprocessing": 4816, |
|
"step": 5926, |
|
"training": 6394, |
|
"feature": 2162, |
|
"models": 3905, |
|
"requires": 5377, |
|
"additional": 191, |
|
"annotated": 344, |
|
"resources": 5413, |
|
"restricts": 5425, |
|
"applicability": 369, |
|
"novel": 4297, |
|
"languages": 3267, |
|
"similarly": 5751, |
|
"introduces": 3008, |
|
"source": 5830, |
|
"error": 1879, |
|
"address": 197, |
|
"limitations": 3463, |
|
"introduce": 3000, |
|
"transformer": 6436, |
|
"extending": 2085, |
|
"openai": 4374, |
|
"generative": 2436, |
|
"radford": 5108, |
|
"et": 1892, |
|
"al": 285, |
|
"2018": 31, |
|
"unlike": 6575, |
|
"previous": 4869, |
|
"uses": 6639, |
|
"deep": 1400, |
|
"instead": 2936, |
|
"explicit": 2060, |
|
"linguistic": 3477, |
|
"classification": 859, |
|
"combines": 942, |
|
"selfattentive": 5616, |
|
"architecture": 424, |
|
"effectively": 1722, |
|
"model": 3809, |
|
"dependencies": 1465, |
|
"entity": 1863, |
|
"mentions": 3728, |
|
"allows": 313, |
|
"learn": 3373, |
|
"implicit": 2771, |
|
"solely": 5811, |
|
"plain": 4695, |
|
"text": 6276, |
|
"corpora": 1195, |
|
"unsupervised": 6592, |
|
"pretraining": 4860, |
|
"finetuning": 2223, |
|
"learned": 3376, |
|
"task": 6143, |
|
"obtains": 4348, |
|
"new": 4242, |
|
"result": 5426, |
|
"datasets": 1365, |
|
"achieving": 157, |
|
"test": 6264, |
|
"f1": 2111, |
|
"respectively": 5416, |
|
"furthermore": 2322, |
|
"observe": 4339, |
|
"significant": 5720, |
|
"increase": 2836, |
|
"sample": 5531, |
|
"efficiency": 1731, |
|
"20": 29, |
|
"examples": 1974, |
|
"matches": 3681, |
|
"performance": 4601, |
|
"baselines": 574, |
|
"trained": 6385, |
|
"scratch": 5583, |
|
"100": 4, |
|
"dataset": 1351, |
|
"opensource": 4389, |
|
"experiments": 2042, |
|
"code": 888, |
|
"supervised": 6066, |
|
"widely": 6805, |
|
"used": 6621, |
|
"extract": 2101, |
|
"relational": 5311, |
|
"facts": 2128, |
|
"suffers": 6034, |
|
"noisy": 4280, |
|
"labels": 3118, |
|
"try": 6493, |
|
"alleviate": 306, |
|
"noise": 4279, |
|
"learning": 3379, |
|
"providing": 5034, |
|
"supporting": 6076, |
|
"contextual": 1148, |
|
"information": 2884, |
|
"efficiently": 1735, |
|
"guide": 2573, |
|
"results": 5430, |
|
"observed": 4342, |
|
"biased": 632, |
|
"recognizing": 5250, |
|
"limited": 3465, |
|
"relations": 5312, |
|
"high": 2621, |
|
"precision": 4786, |
|
"ignoring": 2732, |
|
"long": 3592, |
|
"tail": 6132, |
|
"gap": 2340, |
|
"utilize": 6676, |
|
"gpt": 2492, |
|
"similar": 5745, |
|
"shown": 5700, |
|
"capture": 756, |
|
"notable": 4290, |
|
"commonsense": 957, |
|
"knowledge": 3079, |
|
"hypothesize": 2718, |
|
"important": 2777, |
|
"diverse": 1628, |
|
"setting": 5672, |
|
"predicts": 4805, |
|
"larger": 3335, |
|
"distinct": 1623, |
|
"types": 6509, |
|
"confidence": 1086, |
|
"manual": 3663, |
|
"automated": 503, |
|
"evaluation": 1928, |
|
"shows": 5711, |
|
"achieves": 151, |
|
"score": 5577, |
|
"performs": 4652, |
|
"especially": 1883, |
|
"higher": 2625, |
|
"recall": 5207, |
|
"levels": 3428, |
|
"visual": 6762, |
|
"analysis": 326, |
|
"tool": 6349, |
|
"explore": 2068, |
|
"transformers": 6457, |
|
"large": 3271, |
|
"produce": 4914, |
|
"powerful": 4767, |
|
"lead": 3361, |
|
"improvements": 2797, |
|
"nlp": 4269, |
|
"tasks": 6164, |
|
"guided": 2574, |
|
"sequence": 5651, |
|
"attention": 483, |
|
"mechanisms": 3711, |
|
"inductive": 2866, |
|
"biases": 633, |
|
"paramount": 4549, |
|
"able": 98, |
|
"static": 5920, |
|
"analyses": 325, |
|
"targeted": 6142, |
|
"insights": 2925, |
|
"interactive": 2976, |
|
"tools": 6351, |
|
"dynamic": 1688, |
|
"help": 2609, |
|
"humans": 2704, |
|
"better": 623, |
|
"gain": 2333, |
|
"intuition": 3014, |
|
"reasoning": 5186, |
|
"process": 4902, |
|
"present": 4820, |
|
"named": 4166, |
|
"popular": 4728, |
|
"bert": 612, |
|
"provides": 5030, |
|
"meaning": 3699, |
|
"matching": 3682, |
|
"input": 2913, |
|
"contexts": 1147, |
|
"aggregating": 245, |
|
"annotations": 350, |
|
"helps": 2614, |
|
"explain": 2054, |
|
"answer": 352, |
|
"ask": 449, |
|
"getting": 2464, |
|
"best": 619, |
|
"gpt2": 2502, |
|
"worlds": 6848, |
|
"automatic": 505, |
|
"question": 5094, |
|
"generation": 2406, |
|
"aims": 277, |
|
"questions": 5104, |
|
"context": 1139, |
|
"corresponding": 1211, |
|
"answers": 357, |
|
"given": 2467, |
|
"passage": 4575, |
|
"heuristic": 2617, |
|
"rules": 5523, |
|
"generate": 2370, |
|
"recently": 5229, |
|
"neural": 4228, |
|
"network": 4223, |
|
"approaches": 407, |
|
"proposed": 5005, |
|
"work": 6824, |
|
"propose": 4985, |
|
"variant": 6701, |
|
"selfattention": 5614, |
|
"architectures": 426, |
|
"meaningful": 3700, |
|
"end": 1814, |
|
"easy": 1702, |
|
"use": 6604, |
|
"consisting": 1115, |
|
"conjunction": 1093, |
|
"decoder": 1391, |
|
"encoder": 1801, |
|
"downstream": 1663, |
|
"answering": 354, |
|
"endtoend": 1817, |
|
"representation": 5362, |
|
"facilitates": 2122, |
|
"focused": 2244, |
|
"squad": 5880, |
|
"11": 8, |
|
"suggests": 6042, |
|
"method": 3732, |
|
"semantically": 5627, |
|
"correct": 1199, |
|
"additionally": 194, |
|
"assessed": 459, |
|
"collaboration": 926, |
|
"framework": 2285, |
|
"relatively": 5316, |
|
"improves": 2798, |
|
"particularly": 4568, |
|
"semisupervised": 5636, |
|
"setup": 5675, |
|
"suggest": 6038, |
|
"robust": 5509, |
|
"lean": 3371, |
|
"pipeline": 4687, |
|
"facilitating": 2123, |
|
"regime": 5294, |
|
"efficacy": 1729, |
|
"modern": 4102, |
|
"strategies": 5943, |
|
"continuous": 1153, |
|
"control": 1166, |
|
"optimization": 4410, |
|
"analyze": 337, |
|
"overall": 4470, |
|
"collected": 932, |
|
"wide": 6800, |
|
"variety": 6705, |
|
"qualitatively": 5073, |
|
"different": 1555, |
|
"benchmark": 594, |
|
"problems": 4897, |
|
"indicate": 2854, |
|
"generally": 2368, |
|
"effective": 1716, |
|
"scale": 5545, |
|
"respect": 5414, |
|
"number": 4313, |
|
"parameters": 4542, |
|
"complexity": 1017, |
|
"problem": 4893, |
|
"hyperparameters": 2715, |
|
"comparison": 986, |
|
"promising": 4951, |
|
"indicates": 2856, |
|
"algorithm": 292, |
|
"outperforms": 4452, |
|
"algorithms": 297, |
|
"considered": 1106, |
|
"demonstrate": 1429, |
|
"reward": 5486, |
|
"functions": 2318, |
|
"optimized": 4416, |
|
"reinforcement": 5300, |
|
"necessarily": 4203, |
|
"evolutionary": 1962, |
|
"finding": 2202, |
|
"relative": 5315, |
|
"classes": 856, |
|
"implies": 2773, |
|
"comparisons": 988, |
|
"performed": 4649, |
|
"date": 1374, |
|
"class": 854, |
|
"sentences": 5645, |
|
"modeling": 3902, |
|
"latent": 3351, |
|
"space": 5834, |
|
"autoencoder": 502, |
|
"natural": 4174, |
|
"paper": 4494, |
|
"largescale": 3339, |
|
"universal": 6567, |
|
"embedding": 1749, |
|
"corpus": 1197, |
|
"finetuned": 2214, |
|
"various": 6713, |
|
"understanding": 6538, |
|
"compared": 976, |
|
"enables": 1793, |
|
"abstract": 106, |
|
"level": 3426, |
|
"using": 6643, |
|
"vectors": 6736, |
|
"generalize": 2362, |
|
"lowresource": 3613, |
|
"structure": 5965, |
|
"extensive": 2088, |
|
"experimental": 2034, |
|
"range": 5122, |
|
"effectiveness": 1725, |
|
"benchmarks": 602, |
|
"hope": 2655, |
|
"big": 636, |
|
"community": 961, |
|
"interests": 2980, |
|
"era": 1877, |
|
"make": 3649, |
|
"practical": 4777, |
|
"probabilistically": 4888, |
|
"masked": 3674, |
|
"capable": 749, |
|
"autoregressive": 523, |
|
"arbitrary": 421, |
|
"word": 6816, |
|
"order": 4423, |
|
"line": 3472, |
|
"nlu": 4277, |
|
"nlg": 4267, |
|
"scheme": 5568, |
|
"implement": 2761, |
|
"specific": 5853, |
|
"uniform": 6560, |
|
"prior": 4884, |
|
"distribution": 1625, |
|
"ratio": 5149, |
|
"prove": 5021, |
|
"equivalent": 1876, |
|
"main": 3637, |
|
"advantage": 229, |
|
"supports": 6077, |
|
"surprisingly": 6086, |
|
"good": 2486, |
|
"quality": 5074, |
|
"potentially": 4760, |
|
"enable": 1790, |
|
"applications": 373, |
|
"traditional": 6373, |
|
"unidirectional": 6557, |
|
"data": 1293, |
|
"augmented": 499, |
|
"realworld": 5176, |
|
"challenging": 810, |
|
"deal": 1378, |
|
"imbalance": 2745, |
|
"issues": 3039, |
|
"simple": 5754, |
|
"augment": 494, |
|
"properly": 4981, |
|
"generated": 2385, |
|
"combination": 938, |
|
"gold": 2485, |
|
"train": 6377, |
|
"bertbased": 618, |
|
"classifier": 867, |
|
"series": 5660, |
|
"advantages": 230, |
|
"leads": 3366, |
|
"points": 4715, |
|
"strong": 5953, |
|
"baseline": 570, |
|
"state": 5898, |
|
"art": 437, |
|
"biomedical": 652, |
|
"surpassing": 6083, |
|
"average": 536, |
|
"paraphrase": 4551, |
|
"proven": 5023, |
|
"approach": 389, |
|
"openais": 4377, |
|
"capability": 742, |
|
"fluent": 2242, |
|
"formulated": 2270, |
|
"consistent": 1109, |
|
"phrase": 4677, |
|
"completions": 1006, |
|
"leverage": 3429, |
|
"paraphrases": 4553, |
|
"supervision": 6071, |
|
"labelled": 3116, |
|
"examine": 1967, |
|
"compare": 972, |
|
"effect": 1715, |
|
"augmentation": 497, |
|
"decoding": 1394, |
|
"brain": 675, |
|
"understood": 6551, |
|
"mapping": 3669, |
|
"activities": 169, |
|
"active": 166, |
|
"research": 5383, |
|
"area": 429, |
|
"years": 6856, |
|
"case": 773, |
|
"recent": 5209, |
|
"studies": 5976, |
|
"possible": 4744, |
|
"subject": 6000, |
|
"reading": 5162, |
|
"embeddings": 1752, |
|
"designed": 1491, |
|
"processing": 4907, |
|
"limit": 3461, |
|
"ability": 87, |
|
"recover": 5262, |
|
"precise": 4784, |
|
"directly": 1586, |
|
"classify": 869, |
|
"scan": 5556, |
|
"fixed": 2236, |
|
"vocabulary": 6771, |
|
"existing": 2003, |
|
"evaluate": 1902, |
|
"previously": 4876, |
|
"unseen": 6585, |
|
"subjects": 6002, |
|
"argue": 432, |
|
"realistic": 5167, |
|
"top1": 6357, |
|
"top5": 6359, |
|
"accuracy": 130, |
|
"significantly": 5731, |
|
"outperforming": 4450, |
|
"competitive": 997, |
|
"words": 6822, |
|
"way": 6780, |
|
"advance": 221, |
|
"translates": 6463, |
|
"coherent": 922, |
|
"risks": 5500, |
|
"gpt3": 2513, |
|
"advanced": 222, |
|
"expand": 2019, |
|
"potential": 4749, |
|
"assessing": 462, |
|
"experimenting": 2041, |
|
"prompts": 4975, |
|
"representative": 5367, |
|
"narrative": 4172, |
|
"structures": 5969, |
|
"social": 5802, |
|
"interaction": 2974, |
|
"demonstrates": 1456, |
|
"improvement": 2796, |
|
"generating": 2399, |
|
"texts": 6304, |
|
"gpt3s": 2522, |
|
"strength": 5947, |
|
"accurately": 138, |
|
"emulates": 1789, |
|
"content": 1135, |
|
"utilized": 6681, |
|
"individuals": 2860, |
|
"behaviors": 588, |
|
"measures": 3707, |
|
"possibility": 4743, |
|
"unregulated": 6583, |
|
"technology": 6247, |
|
"represents": 5370, |
|
"risk": 5499, |
|
"online": 4365, |
|
"recruitment": 5264, |
|
"absence": 103, |
|
"successful": 6029, |
|
"efficient": 1733, |
|
"little": 3489, |
|
"experimentation": 2040, |
|
"likely": 3460, |
|
"ai": 250, |
|
"stakeholders": 5886, |
|
"investing": 3026, |
|
"soon": 5825, |
|
"building": 706, |
|
"norms": 4289, |
|
"public": 5040, |
|
"policy": 4719, |
|
"educational": 1713, |
|
"influx": 2883, |
|
"machinegenerated": 3628, |
|
"disinformation": 1608, |
|
"propaganda": 4979, |
|
"mitigation": 3793, |
|
"require": 5373, |
|
"industry": 2871, |
|
"civil": 851, |
|
"society": 5806, |
|
"news": 4263, |
|
"stories": 5938, |
|
"majority": 3648, |
|
"american": 320, |
|
"internet": 2987, |
|
"products": 4926, |
|
"goal": 2482, |
|
"users": 6635, |
|
"lack": 3123, |
|
"scalable": 5544, |
|
"reliable": 5325, |
|
"measuring": 3708, |
|
"metrics": 3766, |
|
"rates": 5146, |
|
"time": 6329, |
|
"track": 6367, |
|
"study": 5978, |
|
"survey": 6087, |
|
"particular": 4563, |
|
"formulate": 2269, |
|
"sequencetosequence": 5655, |
|
"questionanswer": 5099, |
|
"incorrect": 2833, |
|
"intended": 2967, |
|
"containing": 1133, |
|
"human": 2660, |
|
"written": 6853, |
|
"pairs": 4489, |
|
"article": 438, |
|
"summaries": 6047, |
|
"techniques": 6242, |
|
"applying": 387, |
|
"encoderdecoder": 1802, |
|
"t5": 6122, |
|
"outperform": 4444, |
|
"raters": 5145, |
|
"provide": 5025, |
|
"running": 5525, |
|
"google": 2488, |
|
"platform": 4700, |
|
"course": 1227, |
|
"months": 4120, |
|
"automatically": 514, |
|
"finally": 2197, |
|
"serve": 5661, |
|
"controlled": 1171, |
|
"experts": 2053, |
|
"despite": 1500, |
|
"advances": 227, |
|
"remains": 5334, |
|
"attributes": 491, |
|
"expert": 2049, |
|
"lms": 3581, |
|
"andor": 342, |
|
"product": 4923, |
|
"ensemble": 1853, |
|
"tokens": 6348, |
|
"probability": 4890, |
|
"unlikely": 6579, |
|
"apply": 386, |
|
"detoxification": 1517, |
|
"controllable": 1169, |
|
"evaluations": 1953, |
|
"operates": 4396, |
|
"output": 4462, |
|
"lm": 3580, |
|
"smaller": 5795, |
|
"size": 5777, |
|
"including": 2817, |
|
"operating": 4397, |
|
"highlights": 2634, |
|
"promise": 4949, |
|
"tuning": 6497, |
|
"small": 5788, |
|
"undesirable": 6554, |
|
"inverse": 3017, |
|
"objective": 4332, |
|
"estimate": 1888, |
|
"unknown": 6569, |
|
"cost": 1214, |
|
"function": 2311, |
|
"base": 554, |
|
"trajectories": 6431, |
|
"approximate": 416, |
|
"optimal": 4409, |
|
"policies": 4718, |
|
"classical": 858, |
|
"consists": 1116, |
|
"associated": 472, |
|
"cumulative": 1263, |
|
"rl": 5501, |
|
"loss": 3602, |
|
"ones": 4362, |
|
"contributions": 1165, |
|
"degenerate": 1418, |
|
"solutions": 5813, |
|
"algorithmic": 294, |
|
"scalability": 5543, |
|
"quite": 5107, |
|
"bias": 631, |
|
"longer": 3595, |
|
"times": 6335, |
|
"value": 6696, |
|
"based": 557, |
|
"issue": 3033, |
|
"solving": 5823, |
|
"point": 4714, |
|
"stronger": 5961, |
|
"defined": 1416, |
|
"alternative": 315, |
|
"weights": 6797, |
|
"future": 2327, |
|
"states": 5919, |
|
"yields": 6864, |
|
"maximum": 3695, |
|
"entropy": 1867, |
|
"devised": 1538, |
|
"exhibit": 1997, |
|
"enhanced": 1844, |
|
"performances": 4647, |
|
"offtheshelf": 4361, |
|
"multiple": 4149, |
|
"environments": 1870, |
|
"offline": 4359, |
|
"exploratory": 2067, |
|
"demonstrations": 1460, |
|
"available": 529, |
|
"sampling": 5535, |
|
"observations": 4338, |
|
"impossible": 2782, |
|
"operation": 4398, |
|
"costly": 1217, |
|
"ethical": 1899, |
|
"solve": 5814, |
|
"provided": 5028, |
|
"seldom": 5605, |
|
"practice": 4781, |
|
"reasonable": 5185, |
|
"query": 5091, |
|
"addition": 189, |
|
"wrt": 6855, |
|
"behaviour": 589, |
|
"does": 1643, |
|
"imitation": 2748, |
|
"discriminates": 1595, |
|
"inspired": 2930, |
|
"success": 6018, |
|
"settings": 5674, |
|
"exploit": 2062, |
|
"procedures": 4901, |
|
"construct": 1124, |
|
"obtained": 4346, |
|
"outperformed": 4449, |
|
"aforementioned": 236, |
|
"expansion": 2022, |
|
"spoken": 5875, |
|
"queries": 5090, |
|
"intent": 2969, |
|
"detection": 1509, |
|
"conditioned": 1076, |
|
"short": 5689, |
|
"length": 3422, |
|
"regarding": 5292, |
|
"enhance": 1841, |
|
"called": 724, |
|
"utilizes": 6682, |
|
"avoid": 539, |
|
"condition": 1074, |
|
"structured": 5966, |
|
"prompt": 4958, |
|
"zeroshot": 6868, |
|
"oneshot": 4363, |
|
"fewshot": 2173, |
|
"lastly": 3348, |
|
"finetune": 2210, |
|
"roberta": 5506, |
|
"improved": 2794, |
|
"generalpurpose": 2369, |
|
"questionanswering": 5101, |
|
"successes": 6028, |
|
"highquality": 2638, |
|
"qa": 5065, |
|
"systems": 6112, |
|
"freely": 2300, |
|
"response": 5418, |
|
"versatile": 6745, |
|
"making": 3654, |
|
"built": 709, |
|
"exhibits": 2001, |
|
"topics": 6362, |
|
"10": 2, |
|
"absolute": 104, |
|
"suite": 6045, |
|
"challenge": 802, |
|
"magnitude": 3633, |
|
"billion": 641, |
|
"vs": 6774, |
|
"175": 21, |
|
"permutations": 4657, |
|
"inputs": 2922, |
|
"outputs": 4464, |
|
"example": 1972, |
|
"options": 4421, |
|
"illustrate": 2735, |
|
"produces": 4921, |
|
"outside": 4466, |
|
"identify": 2727, |
|
"appears": 368, |
|
"struggle": 5970, |
|
"offering": 4355, |
|
"proves": 5024, |
|
"useful": 6626, |
|
"comprehensive": 1032, |
|
"instruction": 2938, |
|
"taskoriented": 6162, |
|
"dialog": 1540, |
|
"labeling": 3114, |
|
"modules": 4110, |
|
"tod": 6341, |
|
"major": 3646, |
|
"labeled": 3111, |
|
"prompting": 4966, |
|
"plms": 4712, |
|
"power": 4761, |
|
"proposes": 5012, |
|
"exploits": 2064, |
|
"extra": 2100, |
|
"taskspecific": 6225, |
|
"instructions": 2944, |
|
"design": 1487, |
|
"schema": 5567, |
|
"constraint": 1122, |
|
"customized": 1285, |
|
"tracking": 6368, |
|
"adopted": 218, |
|
"unified": 6558, |
|
"conducted": 1083, |
|
"scenarios": 5561, |
|
"validation": 6692, |
|
"empirical": 1773, |
|
"consistently": 1112, |
|
"raw": 5151, |
|
"knowledgebased": 3107, |
|
"involves": 3030, |
|
"external": 2097, |
|
"image": 2737, |
|
"retrieve": 5464, |
|
"reason": 5184, |
|
"selected": 5607, |
|
"prediction": 4794, |
|
"twostep": 6507, |
|
"retrieved": 5465, |
|
"irrelevant": 3032, |
|
"deviate": 1534, |
|
"original": 4436, |
|
"kb": 3061, |
|
"captions": 755, |
|
"retrieval": 5457, |
|
"treat": 6472, |
|
"unstructured": 6588, |
|
"jointly": 3055, |
|
"acquire": 160, |
|
"relevant": 5322, |
|
"specifically": 5860, |
|
"convert": 1186, |
|
"tags": 6131, |
|
"understand": 6537, |
|
"adapt": 173, |
|
"manner": 3662, |
|
"just": 3060, |
|
"incontext": 2824, |
|
"boost": 662, |
|
"carefully": 765, |
|
"investigating": 3023, |
|
"formats": 2267, |
|
"ii": 2733, |
|
"multimodal": 4141, |
|
"16": 19, |
|
"surpasses": 6082, |
|
"decent": 1383, |
|
"foundation": 2278, |
|
"education": 1712, |
|
"stanford": 5892, |
|
"report": 5354, |
|
"2021": 34, |
|
"opportunities": 4404, |
|
"believed": 593, |
|
"represent": 5361, |
|
"paradigm": 4531, |
|
"shift": 5687, |
|
"domains": 1655, |
|
"field": 2181, |
|
"term": 6257, |
|
"describes": 1478, |
|
"broad": 696, |
|
"adapted": 179, |
|
"encompass": 1807, |
|
"computer": 1055, |
|
"vision": 6757, |
|
"technologies": 6246, |
|
"broadly": 700, |
|
"domain": 1648, |
|
"benefits": 609, |
|
"learners": 3378, |
|
"33": 47, |
|
"computational": 1045, |
|
"rapidly": 5140, |
|
"evidence": 1960, |
|
"achieve": 140, |
|
"stated": 5904, |
|
"predict": 4790, |
|
"predictions": 4803, |
|
"intuitive": 3015, |
|
"currently": 1277, |
|
"humanwritten": 2709, |
|
"explanations": 2059, |
|
"hinders": 2647, |
|
"broader": 698, |
|
"usage": 6601, |
|
"standardized": 5889, |
|
"collection": 935, |
|
"right": 5495, |
|
"extensively": 2095, |
|
"exploring": 2074, |
|
"scaling": 5550, |
|
"progress": 4937, |
|
"room": 5515, |
|
"annotators": 351, |
|
"law": 3356, |
|
"recommendation": 5252, |
|
"user": 6628, |
|
"advancement": 224, |
|
"gopher": 2491, |
|
"recognition": 5245, |
|
"remain": 5331, |
|
"scales": 5549, |
|
"areas": 431, |
|
"computation": 1043, |
|
"contrastive": 1156, |
|
"optimizes": 4418, |
|
"taskagnostic": 6161, |
|
"objectives": 4335, |
|
"resulting": 5428, |
|
"great": 2550, |
|
"companies": 965, |
|
"experiment": 2032, |
|
"ctr": 1261, |
|
"investigate": 3018, |
|
"factors": 2127, |
|
"capacity": 753, |
|
"batch": 578, |
|
"discuss": 1599, |
|
"impacts": 2758, |
|
"general": 2348, |
|
"feedback": 2167, |
|
"longform": 3596, |
|
"textbased": 6301, |
|
"environment": 1869, |
|
"search": 5588, |
|
"web": 6793, |
|
"optimize": 4415, |
|
"factual": 2129, |
|
"easier": 1696, |
|
"collect": 930, |
|
"references": 5281, |
|
"browsing": 701, |
|
"support": 6074, |
|
"asked": 450, |
|
"reddit": 5268, |
|
"behavior": 585, |
|
"performing": 4651, |
|
"rejection": 5307, |
|
"preferences": 4808, |
|
"56": 66, |
|
"compute": 1051, |
|
"budget": 702, |
|
"undertrained": 6553, |
|
"consequence": 1099, |
|
"focus": 2243, |
|
"keeping": 3062, |
|
"constant": 1119, |
|
"400": 56, |
|
"ranging": 5130, |
|
"70": 73, |
|
"million": 3772, |
|
"500": 64, |
|
"scaled": 5548, |
|
"equally": 1873, |
|
"hypothesis": 2717, |
|
"predicted": 4792, |
|
"chinchilla": 844, |
|
"4times": 62, |
|
"175b": 24, |
|
"means": 3702, |
|
"substantially": 6013, |
|
"inference": 2874, |
|
"greatly": 2554, |
|
"highlight": 2630, |
|
"reaches": 5154, |
|
"mmlu": 3803, |
|
"leveraging": 3437, |
|
"conversational": 1179, |
|
"seeking": 5601, |
|
"construction": 1127, |
|
"opening": 4384, |
|
"perspectives": 4666, |
|
"description": 1480, |
|
"documents": 1641, |
|
"incremental": 2846, |
|
"oriented": 4434, |
|
"native": 4173, |
|
"inject": 2907, |
|
"conceptual": 1060, |
|
"definitions": 1417, |
|
"samples": 5534, |
|
"usefulness": 6627, |
|
"contribute": 1158, |
|
"posed": 4734, |
|
"flow": 2240, |
|
"needs": 4217, |
|
"fully": 2309, |
|
"customizable": 1284, |
|
"open": 4368, |
|
"actively": 168, |
|
"academic": 110, |
|
"industrial": 2868, |
|
"fields": 2188, |
|
"exist": 2002, |
|
"frameworks": 2297, |
|
"developed": 1521, |
|
"researchers": 5400, |
|
"students": 5974, |
|
"want": 6778, |
|
"developing": 1524, |
|
"implemented": 2766, |
|
"pytorch": 5064, |
|
"include": 2814, |
|
"mujoco": 4128, |
|
"super": 6061, |
|
"components": 1021, |
|
"agent": 239, |
|
"easily": 1697, |
|
"modify": 4106, |
|
"expect": 2023, |
|
"following": 2249, |
|
"github": 2466, |
|
"conditional": 1075, |
|
"media": 3712, |
|
"facto": 2125, |
|
"globally": 2478, |
|
"decade": 1382, |
|
"purpose": 5055, |
|
"intentions": 2971, |
|
"consumers": 1129, |
|
"sources": 5833, |
|
"entities": 1862, |
|
"bring": 693, |
|
"characterizing": 823, |
|
"tweets": 6503, |
|
"openended": 4383, |
|
"fact": 2124, |
|
"probing": 4892, |
|
"capabilities": 728, |
|
"characterize": 821, |
|
"logical": 3589, |
|
"prefixes": 4809, |
|
"sufficiently": 6036, |
|
"subjective": 6001, |
|
"second": 5595, |
|
"positive": 4740, |
|
"qualitative": 5070, |
|
"differences": 1554, |
|
"autonomous": 521, |
|
"agents": 240, |
|
"focusing": 2246, |
|
"strategy": 5944, |
|
"ppo": 4776, |
|
"families": 2148, |
|
"differ": 1552, |
|
"sparse": 5840, |
|
"rewards": 5490, |
|
"iii": 2734, |
|
"discover": 1591, |
|
"minimal": 3780, |
|
"iv": 3049, |
|
"dependency": 1466, |
|
"variations": 6704, |
|
"conditions": 1077, |
|
"behavioral": 586, |
|
"identified": 2726, |
|
"weakness": 6787, |
|
"ways": 6784, |
|
"characteristics": 820, |
|
"impact": 2753, |
|
"vary": 6729, |
|
"demonstrating": 1457, |
|
"importance": 2775, |
|
"optimizing": 4419, |
|
"characteristic": 819, |
|
"medical": 3713, |
|
"scientific": 5574, |
|
"humanintheloop": 2699, |
|
"sparsity": 5842, |
|
"tabular": 6125, |
|
"clinical": 876, |
|
"contains": 1134, |
|
"valuable": 6694, |
|
"summarization": 6048, |
|
"drastically": 1675, |
|
"reduce": 5269, |
|
"efforts": 1740, |
|
"reports": 5358, |
|
"heavily": 2606, |
|
"inability": 2809, |
|
"gptneo": 2529, |
|
"accurate": 137, |
|
"tackle": 6126, |
|
"mechanism": 3709, |
|
"synthetic": 6105, |
|
"selects": 5612, |
|
"salient": 5530, |
|
"values": 6697, |
|
"lightweight": 3448, |
|
"adaptation": 176, |
|
"40": 55, |
|
"validated": 6690, |
|
"scenario": 5560, |
|
"evaluators": 1955, |
|
"write": 6850, |
|
"critical": 1249, |
|
"comments": 949, |
|
"flaws": 2237, |
|
"naturally": 4195, |
|
"properties": 4982, |
|
"helpful": 2611, |
|
"having": 2601, |
|
"integrate": 2956, |
|
"refining": 5288, |
|
"motivate": 4122, |
|
"comparing": 984, |
|
"discrimination": 1596, |
|
"measurements": 3706, |
|
"articulate": 441, |
|
"proof": 4978, |
|
"concept": 1058, |
|
"aiassisted": 267, |
|
"machine": 3618, |
|
"difficult": 1573, |
|
"release": 5317, |
|
"assistance": 469, |
|
"recipe": 5240, |
|
"availability": 528, |
|
"recipes": 5243, |
|
"growing": 2566, |
|
"create": 1238, |
|
"come": 946, |
|
"application": 372, |
|
"teacher": 6231, |
|
"transfer": 6432, |
|
"remarkable": 5337, |
|
"gains": 2337, |
|
"realized": 5171, |
|
"massive": 3676, |
|
"amounts": 321, |
|
"distilling": 1621, |
|
"compact": 964, |
|
"deployment": 1473, |
|
"necessitates": 4206, |
|
"unlabeled": 6570, |
|
"leverages": 3431, |
|
"need": 4208, |
|
"volume": 6773, |
|
"underlying": 6530, |
|
"lower": 3609, |
|
"gradientbased": 2536, |
|
"attractive": 488, |
|
"benefit": 608, |
|
"exploration": 2065, |
|
"generalization": 2358, |
|
"bounds": 674, |
|
"improve": 2790, |
|
"discovery": 1593, |
|
"fundamental": 2319, |
|
"increasingly": 2841, |
|
"utterances": 6686, |
|
"twostage": 6505, |
|
"relying": 5330, |
|
"adapters": 181, |
|
"2020": 33, |
|
"initially": 2906, |
|
"later": 3353, |
|
"applied": 381, |
|
"firstly": 2234, |
|
"adaptive": 184, |
|
"known": 3108, |
|
"showing": 5699, |
|
"perform": 4595, |
|
"equal": 1872, |
|
"ground": 2557, |
|
"truth": 6492, |
|
"holds": 2653, |
|
"customer": 1281, |
|
"care": 763, |
|
"deployed": 1470, |
|
"business": 713, |
|
"considering": 1107, |
|
"hardware": 2596, |
|
"low": 3606, |
|
"resource": 5408, |
|
"cloud": 884, |
|
"imperative": 2759, |
|
"predicting": 4793, |
|
"single": 5772, |
|
"utterance": 6685, |
|
"innovative": 2911, |
|
"enabling": 1796, |
|
"python": 5062, |
|
"package": 4484, |
|
"link": 3480, |
|
"readability": 5157, |
|
"assessment": 463, |
|
"german": 2463, |
|
"translation": 6465, |
|
"allowing": 310, |
|
"develop": 1518, |
|
"contribution": 1162, |
|
"studied": 5975, |
|
"reliably": 5326, |
|
"combined": 941, |
|
"investigated": 3021, |
|
"dependence": 1464, |
|
"composition": 1026, |
|
"mixed": 3794, |
|
"evaluated": 1917, |
|
"2022": 35, |
|
"shared": 5680, |
|
"achieved": 147, |
|
"root": 5517, |
|
"mean": 3698, |
|
"trends": 6483, |
|
"everlarger": 1958, |
|
"huge": 2658, |
|
"prohibitively": 4942, |
|
"expensive": 2026, |
|
"motivating": 4124, |
|
"hyperparameter": 2714, |
|
"offers": 4358, |
|
"tune": 6494, |
|
"generalizes": 2365, |
|
"bayesian": 581, |
|
"schedules": 5565, |
|
"concurrently": 1073, |
|
"global": 2477, |
|
"rate": 5143, |
|
"follow": 2247, |
|
"explainable": 2056, |
|
"greedy": 2555, |
|
"facilitate": 2118, |
|
"retrievalbased": 5462, |
|
"primarily": 4878, |
|
"networks": 4227, |
|
"simultaneously": 5771, |
|
"parallel": 4535, |
|
"augmenting": 500, |
|
"instance": 2934, |
|
"instances": 2935, |
|
"augmentations": 498, |
|
"component": 1020, |
|
"remarkably": 5340, |
|
"standard": 5887, |
|
"protein": 5019, |
|
"demonstrated": 1449, |
|
"literature": 3487, |
|
"showcasing": 5697, |
|
"theoretical": 6314, |
|
"underpinning": 6532, |
|
"formal": 2262, |
|
"treatment": 6474, |
|
"local": 3582, |
|
"employs": 1784, |
|
"subtasks": 6016, |
|
"employ": 1780, |
|
"parametric": 4548, |
|
"ensure": 1854, |
|
"learns": 3418, |
|
"kernel": 3064, |
|
"map": 3668, |
|
"bases": 575, |
|
"incomplete": 2821, |
|
"contextually": 1151, |
|
"starts": 5897, |
|
"imitating": 2747, |
|
"increased": 2838, |
|
"substantial": 6012, |
|
"tested": 6273, |
|
"seen": 5602, |
|
"kept": 3063, |
|
"orders": 4429, |
|
"direct": 1582, |
|
"exceed": 1977, |
|
"temporal": 6251, |
|
"disambiguation": 1587, |
|
"changes": 817, |
|
"events": 1957, |
|
"change": 815, |
|
"resolve": 5407, |
|
"ambiguity": 318, |
|
"effort": 1737, |
|
"direction": 1584, |
|
"sense": 5639, |
|
"conduct": 1078, |
|
"ablations": 97, |
|
"directions": 1585, |
|
"helped": 2610, |
|
"numerous": 4327, |
|
"opened": 4382, |
|
"door": 1662, |
|
"development": 1525, |
|
"modalities": 3806, |
|
"images": 2742, |
|
"music": 4163, |
|
"unique": 6563, |
|
"handle": 2591, |
|
"like": 3449, |
|
"decision": 1386, |
|
"challenges": 805, |
|
"processes": 4906, |
|
"scarcity": 5558, |
|
"terminology": 6260, |
|
"privacy": 4886, |
|
"concerns": 1066, |
|
"knowledgeable": 3105, |
|
"semiparametric": 5632, |
|
"fullyparametric": 2310, |
|
"store": 5936, |
|
"necessary": 4204, |
|
"hard": 2593, |
|
"evolving": 1963, |
|
"world": 6846, |
|
"retraining": 5456, |
|
"empowers": 1788, |
|
"texttotext": 6307, |
|
"memory": 3722, |
|
"event": 1956, |
|
"adaptively": 185, |
|
"type": 6508, |
|
"retrieves": 5468, |
|
"pieces": 4683, |
|
"forms": 2268, |
|
"special": 5850, |
|
"mixtureofexperts": 3798, |
|
"moe": 4111, |
|
"plays": 4705, |
|
"role": 5512, |
|
"determine": 1514, |
|
"assignment": 466, |
|
"key": 3065, |
|
"observation": 4337, |
|
"inspires": 2931, |
|
"superior": 6063, |
|
"evaluating": 1921, |
|
"770m": 75, |
|
"margin": 3671, |
|
"emergent": 1760, |
|
"abilities": 85, |
|
"failure": 2135, |
|
"gained": 2334, |
|
"stems": 5925, |
|
"innovation": 2909, |
|
"introduced": 3007, |
|
"recurrent": 5266, |
|
"lstm": 3617, |
|
"causal": 782, |
|
"steps": 5931, |
|
"analyzing": 340, |
|
"semiconductor": 5630, |
|
"15b": 17, |
|
"bart": 553, |
|
"rouge": 5519, |
|
"sequential": 5657, |
|
"metric": 3764, |
|
"compares": 983, |
|
"exactly": 1965, |
|
"ignore": 2731, |
|
"transformerbased": 6446, |
|
"llms": 3511, |
|
"vulnerabilities": 6776, |
|
"emerging": 1764, |
|
"scarce": 5557, |
|
"proposing": 5015, |
|
"alignment": 303, |
|
"iterative": 3046, |
|
"adversarial": 232, |
|
"production": 4924, |
|
"handcrafted": 2590, |
|
"attacks": 479, |
|
"leaking": 3370, |
|
"stochastic": 5933, |
|
"nature": 4196, |
|
"creating": 1242, |
|
"legal": 3421, |
|
"engineering": 1827, |
|
"multilingual": 4135, |
|
"assist": 468, |
|
"llm": 3496, |
|
"skill": 5783, |
|
"european": 1901, |
|
"english": 1837, |
|
"french": 2302, |
|
"italian": 3042, |
|
"falls": 2144, |
|
"domainspecific": 1659, |
|
"turn": 6499, |
|
"saves": 5541, |
|
"terms": 6261, |
|
"costs": 1218, |
|
"evolution": 1961, |
|
"dissemination": 1611, |
|
"effects": 1728, |
|
"platforms": 4701, |
|
"real": 5165, |
|
"detecting": 1508, |
|
"reasons": 5206, |
|
"emerge": 1757, |
|
"cultural": 1262, |
|
"ideas": 2720, |
|
"systematically": 6110, |
|
"relationships": 5314, |
|
"modality": 3807, |
|
"property": 4983, |
|
"created": 1240, |
|
"combining": 945, |
|
"elements": 1742, |
|
"textual": 6310, |
|
"extracted": 2102, |
|
"variants": 6702, |
|
"organizations": 4432, |
|
"envision": 1871, |
|
"aid": 269, |
|
"manually": 3665, |
|
"verify": 6743, |
|
"mitigate": 3790, |
|
"scoring": 5581, |
|
"stepbystep": 5927, |
|
"prompted": 4965, |
|
"final": 2196, |
|
"interpretability": 2990, |
|
"verification": 6740, |
|
"objectively": 4334, |
|
"studying": 5993, |
|
"correctness": 1204, |
|
"independent": 2849, |
|
"simply": 5763, |
|
"know": 3077, |
|
"actually": 171, |
|
"interpretable": 2991, |
|
"scores": 5580, |
|
"extend": 2082, |
|
"errors": 1881, |
|
"commonly": 955, |
|
"contrast": 1155, |
|
"measure": 3704, |
|
"consistency": 1108, |
|
"informativeness": 2897, |
|
"fluency": 2241, |
|
"factuality": 2131, |
|
"traits": 6430, |
|
"rationales": 5150, |
|
"empirically": 1779, |
|
"perturbed": 4671, |
|
"covering": 1232, |
|
"skills": 5785, |
|
"mental": 3726, |
|
"everyday": 1959, |
|
"people": 4588, |
|
"think": 6317, |
|
"correctly": 1203, |
|
"judge": 3057, |
|
"false": 2146, |
|
"picture": 4682, |
|
"parts": 4570, |
|
"expressed": 2077, |
|
"extension": 2087, |
|
"add": 186, |
|
"layer": 3359, |
|
"constraints": 1123, |
|
"removing": 5342, |
|
"inconsistencies": 2823, |
|
"suggesting": 6040, |
|
"reduced": 5272, |
|
"chatbots": 827, |
|
"cybersecurity": 1287, |
|
"latest": 3354, |
|
"chatgpt": 828, |
|
"complex": 1007, |
|
"coding": 913, |
|
"qualify": 5069, |
|
"stages": 5885, |
|
"access": 116, |
|
"defense": 1413, |
|
"varying": 6730, |
|
"logic": 3588, |
|
"cases": 776, |
|
"functionality": 2314, |
|
"goals": 2484, |
|
"surprising": 6085, |
|
"languageonly": 3266, |
|
"yield": 6862, |
|
"programming": 4932, |
|
"links": 3482, |
|
"offer": 4353, |
|
"interface": 2981, |
|
"cyber": 1286, |
|
"security": 5599, |
|
"commands": 948, |
|
"actions": 165, |
|
"attackers": 478, |
|
"insight": 2924, |
|
"feasibility": 2160, |
|
"meant": 3703, |
|
"teams": 6237, |
|
"mimic": 3777, |
|
"expected": 2024, |
|
"interfaces": 2983, |
|
"ultimately": 6518, |
|
"reaching": 5155, |
|
"databases": 1348, |
|
"confidential": 1087, |
|
"ongoing": 4364, |
|
"maintenance": 3645, |
|
"monitoring": 4112, |
|
"required": 5375, |
|
"chatgpts": 837, |
|
"detect": 1506, |
|
"makes": 3652, |
|
"option": 4420, |
|
"layers": 3360, |
|
"science": 5571, |
|
"testbeds": 6272, |
|
"publiclyavailable": 5052, |
|
"1000": 5, |
|
"basic": 576, |
|
"arithmetic": 435, |
|
"statistical": 5921, |
|
"described": 1477, |
|
"manipulations": 3661, |
|
"encoded": 1800, |
|
"examines": 1970, |
|
"sentence": 5644, |
|
"completion": 1004, |
|
"realm": 5174, |
|
"actual": 170, |
|
"numerical": 4323, |
|
"statistics": 5922, |
|
"generates": 2398, |
|
"randomly": 5121, |
|
"libraries": 3442, |
|
"showcases": 5696, |
|
"pivot": 4691, |
|
"infer": 2873, |
|
"derive": 1475, |
|
"correlations": 1209, |
|
"linear": 3473, |
|
"regression": 5297, |
|
"random": 5119, |
|
"mitigating": 3792, |
|
"taken": 6135, |
|
"storm": 5939, |
|
"specialized": 5851, |
|
"span": 5836, |
|
"simplification": 5761, |
|
"writing": 6852, |
|
"styles": 5997, |
|
"considerably": 1104, |
|
"multilabel": 4134, |
|
"select": 5606, |
|
"outcome": 4438, |
|
"individual": 2858, |
|
"testing": 6274, |
|
"codebases": 906, |
|
"awareness": 542, |
|
"frequently": 2305, |
|
"axes": 543, |
|
"reliability": 5324, |
|
"secure": 5598, |
|
"standpoint": 5890, |
|
"formulating": 2272, |
|
"takes": 6136, |
|
"binary": 647, |
|
"preserving": 4833, |
|
"functionally": 2315, |
|
"learningbased": 3417, |
|
"program": 4930, |
|
"modifying": 4107, |
|
"procedure": 4900, |
|
"enforcing": 1821, |
|
"regions": 5296, |
|
"curated": 1266, |
|
"highly": 2635, |
|
"codegen": 910, |
|
"boosted": 664, |
|
"importantly": 2781, |
|
"closely": 881, |
|
"functional": 2312, |
|
"brief": 691, |
|
"virtual": 6756, |
|
"assistant": 470, |
|
"helping": 2613, |
|
"overview": 4483, |
|
"note": 4293, |
|
"detailed": 1503, |
|
"agreement": 248, |
|
"reveal": 5472, |
|
"sensitivity": 5642, |
|
"semantics": 5629, |
|
"syntax": 6096, |
|
"involved": 3028, |
|
"speech": 5866, |
|
"comprehension": 1031, |
|
"discourse": 1590, |
|
"extent": 2096, |
|
"intertwined": 2994, |
|
"selectively": 5611, |
|
"signal": 5716, |
|
"listening": 3484, |
|
"manipulated": 3658, |
|
"integration": 2961, |
|
"sensitive": 5640, |
|
"variables": 6700, |
|
"magnitudes": 3636, |
|
"lot": 3605, |
|
"shed": 5683, |
|
"light": 3447, |
|
"spatial": 5843, |
|
"organization": 4431, |
|
"compositionality": 1029, |
|
"enabled": 1792, |
|
"predominantly": 4807, |
|
"approached": 406, |
|
"multitask": 4160, |
|
"referred": 5283, |
|
"core": 1194, |
|
"indicating": 2857, |
|
"complementary": 1000, |
|
"instructionbased": 2942, |
|
"annotation": 349, |
|
"identification": 2725, |
|
"sets": 5671, |
|
"worse": 6849, |
|
"drops": 1686, |
|
"presented": 4828, |
|
"questioning": 5103, |
|
"idea": 2719, |
|
"outlines": 4441, |
|
"involving": 3031, |
|
"intelligent": 2965, |
|
"software": 5807, |
|
"highlevel": 2628, |
|
"chatgptlike": 836, |
|
"today": 6342, |
|
"shortterm": 5693, |
|
"longterm": 3600, |
|
"job": 3051, |
|
"investigates": 3022, |
|
"posting": 4747, |
|
"appropriate": 415, |
|
"position": 4738, |
|
"machines": 3631, |
|
"deberta": 1381, |
|
"accomplish": 123, |
|
"technique": 6241, |
|
"designing": 1496, |
|
"desired": 1499, |
|
"gpt35turbo": 2521, |
|
"aspects": 454, |
|
"wording": 6820, |
|
"factor": 2126, |
|
"minor": 3785, |
|
"affect": 234, |
|
"querying": 5093, |
|
"visualization": 6767, |
|
"powered": 4762, |
|
"sql": 5879, |
|
"summarize": 6056, |
|
"edit": 1708, |
|
"visualizations": 6768, |
|
"flexibility": 2238, |
|
"mind": 3778, |
|
"suitable": 6044, |
|
"analysts": 336, |
|
"reply": 5353, |
|
"artificial": 442, |
|
"intelligence": 2962, |
|
"operations": 4400, |
|
"consolidated": 1118, |
|
"filtering": 2195, |
|
"surge": 6080, |
|
"dramatically": 1674, |
|
"magnifies": 3632, |
|
"aimed": 275, |
|
"increasing": 2840, |
|
"contents": 1138, |
|
"interactions": 2975, |
|
"engage": 1822, |
|
"preliminary": 4810, |
|
"showcase": 5695, |
|
"counteract": 1222, |
|
"threats": 6324, |
|
"implications": 2770, |
|
"addressed": 209, |
|
"perspective": 4663, |
|
"ubiquitous": 6517, |
|
"adoption": 219, |
|
"clear": 873, |
|
"divergence": 1627, |
|
"document": 1638, |
|
"criteria": 1248, |
|
"grammar": 2539, |
|
"adequately": 215, |
|
"dimensions": 1581, |
|
"reference": 5279, |
|
"texttoimage": 6305, |
|
"diffusion": 1577, |
|
"classifiers": 868, |
|
"excellent": 1982, |
|
"informative": 2896, |
|
"imagetext": 2743, |
|
"thoroughly": 6320, |
|
"explored": 2070, |
|
"label": 3110, |
|
"likelihood": 3459, |
|
"stable": 5882, |
|
"imagen": 2740, |
|
"probe": 4891, |
|
"finegrained": 2209, |
|
"competitively": 999, |
|
"tests": 6275, |
|
"successfully": 6031, |
|
"attribute": 490, |
|
"binding": 648, |
|
"prevalent": 4866, |
|
"findings": 2203, |
|
"compelling": 990, |
|
"visionlanguage": 6760, |
|
"gpt4": 2523, |
|
"conventional": 1175, |
|
"bleu": 655, |
|
"correlation": 1208, |
|
"judgments": 3059, |
|
"creativity": 1245, |
|
"diversity": 1634, |
|
"referencefree": 5280, |
|
"applicable": 370, |
|
"llmbased": 3509, |
|
"correspondence": 1210, |
|
"cot": 1219, |
|
"assess": 456, |
|
"dialogue": 1546, |
|
"backbone": 544, |
|
"spearman": 5848, |
|
"llmgenerated": 3510, |
|
"object": 4331, |
|
"database": 1347, |
|
"spanning": 5838, |
|
"emphasizing": 1772, |
|
"exact": 1964, |
|
"uncertain": 6521, |
|
"depends": 1469, |
|
"chosen": 849, |
|
"assumptions": 477, |
|
"review": 5476, |
|
"observing": 4343, |
|
"runs": 5526, |
|
"millions": 3775, |
|
"explorer": 2072, |
|
"publicly": 5047, |
|
"numbers": 4321, |
|
"highlighting": 2633, |
|
"growth": 2568, |
|
"exciting": 1986, |
|
"plan": 4696, |
|
"uptodate": 6599, |
|
"suggestions": 6041, |
|
"demonstration": 1459, |
|
"crucial": 1258, |
|
"interpret": 2989, |
|
"indepth": 2851, |
|
"expertise": 2050, |
|
"familiar": 2147, |
|
"obstacles": 4344, |
|
"timeconsuming": 6333, |
|
"modelbased": 3899, |
|
"simplify": 5762, |
|
"summarizing": 6059, |
|
"abstraction": 107, |
|
"automation": 519, |
|
"employing": 1783, |
|
"iteratively": 3048, |
|
"collaborate": 925, |
|
"engine": 1825, |
|
"pivotal": 4692, |
|
"engines": 1834, |
|
"impressive": 2784, |
|
"tag": 6129, |
|
"tagging": 6130, |
|
"elaborate": 1741, |
|
"proper": 4980, |
|
"ocr": 4351, |
|
"asr": 455, |
|
"title": 6340, |
|
"build": 704, |
|
"reflects": 5290, |
|
"candidate": 726, |
|
"filtered": 2194, |
|
"frequency": 2304, |
|
"late": 3349, |
|
"early": 1693, |
|
"systemlevel": 6111, |
|
"solution": 5812, |
|
"modular": 4108, |
|
"gpt35": 2519, |
|
"seamlessly": 5587, |
|
"replaced": 5351, |
|
"project": 4944, |
|
"page": 4485, |
|
"instructionfollowing": 2943, |
|
"needed": 4215, |
|
"attempt": 481, |
|
"instructiontuned": 2947, |
|
"llama": 3492, |
|
"chinese": 845, |
|
"codebase": 905, |
|
"directed": 1583, |
|
"lowcost": 3608, |
|
"akin": 284, |
|
"fostering": 2277, |
|
"influence": 2882, |
|
"quantity": 5084, |
|
"grounded": 2560, |
|
"accessible": 120, |
|
"multiturn": 4161, |
|
"conversations": 1184, |
|
"encompassing": 1808, |
|
"supplement": 6073, |
|
"quantitative": 5082, |
|
"chat": 825, |
|
"proprietary": 5016, |
|
"comparative": 969, |
|
"instructiontuning": 2950, |
|
"employed": 1782, |
|
"parameterefficient": 4540, |
|
"lora": 3601, |
|
"encouraging": 1812, |
|
"utilizing": 6683, |
|
"selection": 5610, |
|
"foundational": 2280, |
|
"learnable": 3375, |
|
"parameter": 4536, |
|
"conclusions": 1070, |
|
"inspiration": 2928, |
|
"tradeoff": 6372, |
|
"papers": 4529, |
|
"released": 5320, |
|
"theory": 6316, |
|
"adam": 172, |
|
"instability": 2933, |
|
"phenomenon": 4675, |
|
"dominant": 1660, |
|
"update": 6593, |
|
"norm": 4287, |
|
"landscape": 3133, |
|
"leading": 3364, |
|
"typical": 6514, |
|
"30": 45, |
|
"65": 70, |
|
"codebook": 907, |
|
"deductive": 1399, |
|
"rich": 5492, |
|
"assigning": 465, |
|
"laborintensive": 3121, |
|
"working": 6841, |
|
"aibased": 268, |
|
"utility": 6674, |
|
"readily": 5160, |
|
"let": 3425, |
|
"generalizability": 2356, |
|
"category": 781, |
|
"predetermined": 4789, |
|
"codes": 911, |
|
"fair": 2138, |
|
"lay": 3358, |
|
"parsing": 4558, |
|
"followed": 2248, |
|
"retriever": 5466, |
|
"applies": 382, |
|
"combinations": 939, |
|
"retrievers": 5467, |
|
"indomain": 2862, |
|
"candidates": 727, |
|
"regardless": 5293, |
|
"wrong": 6854, |
|
"target": 6139, |
|
"pattern": 4582, |
|
"aware": 541, |
|
"patterns": 4583, |
|
"selfsupervised": 5618, |
|
"bottlenecks": 670, |
|
"bm25": 659, |
|
"module": 4109, |
|
"overlap": 4480, |
|
"literal": 3486, |
|
"bottleneck": 669, |
|
"userprovided": 6634, |
|
"names": 4171, |
|
"cad": 717, |
|
"files": 2192, |
|
"searching": 5594, |
|
"repositories": 5359, |
|
"designers": 1495, |
|
"contain": 1132, |
|
"clean": 872, |
|
"quantitatively": 5083, |
|
"boosts": 665, |
|
"largely": 3334, |
|
"motivation": 4125, |
|
"encourage": 1811, |
|
"ml": 3800, |
|
"widespread": 6808, |
|
"demand": 1424, |
|
"adapting": 182, |
|
"nontrivial": 4285, |
|
"predominant": 4806, |
|
"automl": 520, |
|
"consuming": 1130, |
|
"developers": 1523, |
|
"engineers": 1832, |
|
"incredible": 2845, |
|
"experience": 2028, |
|
"aim": 272, |
|
"bridge": 686, |
|
"introducing": 3012, |
|
"comprehend": 1030, |
|
"dedicated": 1398, |
|
"experiences": 2030, |
|
"quantum": 5088, |
|
"amplified": 323, |
|
"computing": 1057, |
|
"discrete": 1594, |
|
"cyclically": 1288, |
|
"shifting": 5688, |
|
"encoding": 1805, |
|
"graphs": 2546, |
|
"kgs": 3072, |
|
"suffer": 6032, |
|
"subpar": 6006, |
|
"formulates": 2271, |
|
"kg": 3071, |
|
"strengths": 5949, |
|
"graph": 2545, |
|
"proportionally": 4984, |
|
"advancements": 225, |
|
"presents": 4830, |
|
"addressing": 211, |
|
"paves": 4584, |
|
"lessons": 3423, |
|
"synthesis": 6097, |
|
"laws": 3357, |
|
"upper": 6598, |
|
"render": 5343, |
|
"infill": 2881, |
|
"distributions": 1626, |
|
"unify": 6561, |
|
"claim": 852, |
|
"mixture": 3795, |
|
"1b": 28, |
|
"failures": 2137, |
|
"distilled": 1620, |
|
"7b": 78, |
|
"gradient": 2535, |
|
"beam": 582, |
|
"dependent": 1467, |
|
"hand": 2589, |
|
"assuming": 476, |
|
"api": 363, |
|
"form": 2258, |
|
"gradients": 2537, |
|
"editing": 1710, |
|
"opposite": 4407, |
|
"bandit": 548, |
|
"initial": 2904, |
|
"descriptions": 1481, |
|
"distillation": 1615, |
|
"primary": 4880, |
|
"limiting": 3470, |
|
"suspicious": 6089, |
|
"professional": 4927, |
|
"classifications": 865, |
|
"established": 1886, |
|
"student": 5972, |
|
"tailored": 6134, |
|
"classifying": 870, |
|
"telemetry": 6248, |
|
"categories": 780, |
|
"depending": 1468, |
|
"resourceintensive": 5412, |
|
"website": 6796, |
|
"jobs": 3053, |
|
"creates": 1241, |
|
"39": 51, |
|
"exam": 1966, |
|
"preparation": 4812, |
|
"qualifications": 5068, |
|
"repair": 5345, |
|
"scored": 5579, |
|
"offensive": 4352, |
|
"competence": 992, |
|
"teaching": 6235, |
|
"passed": 4576, |
|
"financial": 2201, |
|
"grade": 2534, |
|
"service": 5664, |
|
"routine": 5521, |
|
"services": 5665, |
|
"emotional": 1767, |
|
"body": 660, |
|
"resulted": 5427, |
|
"60": 68, |
|
"shortcomings": 5692, |
|
"performant": 4648, |
|
"rating": 5147, |
|
"exceptional": 1983, |
|
"generalizing": 2367, |
|
"unclear": 6526, |
|
"traditionally": 6376, |
|
"collaborative": 928, |
|
"maintaining": 3642, |
|
"item": 3043, |
|
"classic": 857, |
|
"past": 4577, |
|
"ratings": 5148, |
|
"sizes": 5781, |
|
"540b": 65, |
|
"recommender": 5255, |
|
"comparable": 967, |
|
"fraction": 2281, |
|
"arc": 422, |
|
"concepts": 1059, |
|
"lacking": 3129, |
|
"progressive": 4940, |
|
"matrices": 3691, |
|
"rarely": 5142, |
|
"depth": 1474, |
|
"2019": 32, |
|
"assesses": 461, |
|
"organized": 4433, |
|
"groups": 2565, |
|
"solvers": 5821, |
|
"programs": 4935, |
|
"competition": 996, |
|
"captured": 757, |
|
"believe": 591, |
|
"zero": 6865, |
|
"providers": 5029, |
|
"customers": 1283, |
|
"face": 2115, |
|
"coldstart": 924, |
|
"storage": 5935, |
|
"degrees": 1421, |
|
"reached": 5153, |
|
"milestones": 3771, |
|
"grand": 2541, |
|
"viewed": 6755, |
|
"style": 5994, |
|
"bridges": 689, |
|
"gaps": 2345, |
|
"palm": 4490, |
|
"refinement": 5286, |
|
"19": 27, |
|
"approaching": 414, |
|
"exceeding": 1978, |
|
"ranking": 5135, |
|
"consumer": 1128, |
|
"produced": 4920, |
|
"pertaining": 4667, |
|
"newly": 4261, |
|
"validate": 6688, |
|
"rapid": 5138, |
|
"details": 1505, |
|
"cover": 1229, |
|
"configuration": 1088, |
|
"forward": 2275, |
|
"exhibited": 1999, |
|
"extended": 2084, |
|
"exploiting": 2063, |
|
"dual": 1687, |
|
"concretely": 1072, |
|
"stage": 5884, |
|
"thinking": 6318, |
|
"stored": 5937, |
|
"summarizer": 6057, |
|
"serving": 5667, |
|
"hinder": 2646, |
|
"utilization": 6675, |
|
"conversely": 1185, |
|
"tend": 6252, |
|
"favor": 2159, |
|
"inferior": 2880, |
|
"derived": 1476, |
|
"purposes": 5056, |
|
"lists": 3485, |
|
"highthroughput": 2645, |
|
"biological": 650, |
|
"framed": 2284, |
|
"avoiding": 540, |
|
"reliance": 5327, |
|
"reporting": 5357, |
|
"plausible": 4702, |
|
"valid": 6687, |
|
"summary": 6060, |
|
"gptbased": 2526, |
|
"unable": 6519, |
|
"return": 5470, |
|
"radically": 5112, |
|
"unsuitable": 6591, |
|
"replacement": 5352, |
|
"curation": 1267, |
|
"rewriting": 5491, |
|
"restricted": 5423, |
|
"apis": 365, |
|
"impractical": 2783, |
|
"pool": 4725, |
|
"refine": 5285, |
|
"rank": 5131, |
|
"combine": 940, |
|
"robustness": 5510, |
|
"minimizing": 3783, |
|
"integrated": 2958, |
|
"plugandplay": 4713, |
|
"health": 2604, |
|
"introduction": 3013, |
|
"covid19": 1233, |
|
"pandemic": 4492, |
|
"highlighted": 2632, |
|
"sharing": 5682, |
|
"included": 2815, |
|
"updated": 6594, |
|
"simplicity": 5760, |
|
"overcome": 4476, |
|
"chatbot": 826, |
|
"453": 61, |
|
"13": 12, |
|
"scope": 5576, |
|
"34": 48, |
|
"processed": 4905, |
|
"interacting": 2973, |
|
"realtime": 5175, |
|
"policymakers": 4722, |
|
"showed": 5698, |
|
"complements": 1001, |
|
"quantifying": 5081, |
|
"checkpoints": 840, |
|
"perturbations": 4670, |
|
"exists": 2018, |
|
"glue": 2479, |
|
"quantify": 5080, |
|
"perturbation": 4669, |
|
"changing": 818, |
|
"characters": 824, |
|
"impactful": 2757, |
|
"weaknesses": 6788, |
|
"cross": 1251, |
|
"difference": 1553, |
|
"selecting": 5608, |
|
"crossentropy": 1253, |
|
"negatively": 4219, |
|
"correlates": 1207, |
|
"perplexity": 4658, |
|
"independently": 2850, |
|
"representing": 5369, |
|
"extremescale": 2110, |
|
"excel": 1981, |
|
"controlling": 1173, |
|
"toxicity": 6366, |
|
"reduction": 5276, |
|
"opendomain": 4381, |
|
"brings": 694, |
|
"essential": 1884, |
|
"debate": 1380, |
|
"exhibiting": 2000, |
|
"comprehensively": 1038, |
|
"location": 3586, |
|
"items": 3044, |
|
"variation": 6703, |
|
"reality": 5169, |
|
"2nd": 43, |
|
"choice": 847, |
|
"chainofthought": 797, |
|
"deeper": 1409, |
|
"personalized": 4662, |
|
"historical": 2649, |
|
"pursue": 5057, |
|
"life": 3446, |
|
"started": 5894, |
|
"live": 3490, |
|
"vertical": 6749, |
|
"nuanced": 4309, |
|
"interesting": 2979, |
|
"define": 1415, |
|
"stepping": 5929, |
|
"stone": 5934, |
|
"entirely": 1861, |
|
"conversation": 1178, |
|
"inferences": 2878, |
|
"vital": 6769, |
|
"grounding": 2561, |
|
"timeseries": 6338, |
|
"sensor": 5643, |
|
"recordings": 5260, |
|
"cardiac": 762, |
|
"physical": 4679, |
|
"estimation": 1890, |
|
"according": 125, |
|
"usually": 6673, |
|
"similarity": 5750, |
|
"sufficient": 6035, |
|
"syntactically": 6095, |
|
"adopt": 217, |
|
"aggregation": 246, |
|
"pseudo": 5037, |
|
"negative": 4218, |
|
"statements": 5905, |
|
"topic": 6361, |
|
"crowdsourced": 1257, |
|
"notion": 4295, |
|
"ambiguous": 319, |
|
"keywords": 3070, |
|
"november": 4307, |
|
"family": 2149, |
|
"received": 5208, |
|
"responses": 5420, |
|
"common": 951, |
|
"breadth": 676, |
|
"resolution": 5406, |
|
"requirements": 5376, |
|
"log": 3587, |
|
"respective": 5415, |
|
"retrievalaugmented": 5461, |
|
"reducing": 5274, |
|
"poses": 4735, |
|
"custom": 1280, |
|
"diffuse": 1576, |
|
"relevance": 5321, |
|
"rated": 5144, |
|
"50": 63, |
|
"43": 59, |
|
"highest": 2627, |
|
"32": 46, |
|
"hallucinations": 2587, |
|
"nonexistent": 4283, |
|
"methodologies": 3749, |
|
"accessing": 121, |
|
"explores": 2073, |
|
"evaluates": 1920, |
|
"clustering": 886, |
|
"discussed": 1602, |
|
"clustered": 885, |
|
"quickly": 5106, |
|
"automating": 518, |
|
"educators": 1714, |
|
"readers": 5159, |
|
"hold": 2651, |
|
"enhancing": 1848, |
|
"synthesizing": 6104, |
|
"seek": 5600, |
|
"specification": 5863, |
|
"synthesize": 6102, |
|
"symbolic": 6092, |
|
"execution": 1990, |
|
"hour": 2656, |
|
"extracting": 2103, |
|
"accelerate": 112, |
|
"check": 839, |
|
"paving": 4586, |
|
"trustworthy": 6491, |
|
"resourceconstrained": 5410, |
|
"vast": 6733, |
|
"explanation": 2057, |
|
"drawing": 1678, |
|
"signals": 5717, |
|
"shallow": 5678, |
|
"notably": 4291, |
|
"imitate": 2746, |
|
"team": 6236, |
|
"llamas": 3495, |
|
"published": 5053, |
|
"thought": 6321, |
|
"promote": 4956, |
|
"bigbench": 637, |
|
"42": 58, |
|
"radiology": 5113, |
|
"bloomz": 658, |
|
"possess": 4741, |
|
"verbose": 6737, |
|
"mainly": 3640, |
|
"insufficient": 2955, |
|
"ranks": 5137, |
|
"participating": 4561, |
|
"2023": 38, |
|
"workshop": 6845, |
|
"cognitive": 916, |
|
"mathematical": 3688, |
|
"turned": 6500, |
|
"psychological": 5038, |
|
"decisionmaking": 1388, |
|
"transform": 6435, |
|
"psychology": 5039, |
|
"sciences": 5573, |
|
"ner": 4222, |
|
"crosslingual": 1254, |
|
"nonenglish": 4281, |
|
"thanks": 6313, |
|
"translating": 6464, |
|
"guidelines": 2579, |
|
"monolingual": 4113, |
|
"measurement": 3705, |
|
"certain": 794, |
|
"fail": 2132, |
|
"estimating": 1889, |
|
"35": 49, |
|
"prominent": 4948, |
|
"discovering": 1592, |
|
"capturing": 759, |
|
"circumstances": 850, |
|
"purely": 5054, |
|
"imply": 2774, |
|
"assume": 473, |
|
"snippets": 5800, |
|
"situations": 5776, |
|
"guess": 2571, |
|
"competing": 994, |
|
"13b": 14, |
|
"days": 1377, |
|
"6b": 72, |
|
"exercises": 1996, |
|
"attains": 480, |
|
"pass1": 4572, |
|
"humaneval": 2697, |
|
"mbpp": 3696, |
|
"displays": 1610, |
|
"45": 60, |
|
"manipulation": 3659, |
|
"threat": 6323, |
|
"agency": 238, |
|
"near": 4201, |
|
"skillfully": 5784, |
|
"misinformation": 3786, |
|
"revealing": 5473, |
|
"personal": 4660, |
|
"lamda": 3132, |
|
"safe": 5528, |
|
"voice": 6772, |
|
"digital": 1579, |
|
"express": 2076, |
|
"pose": 4733, |
|
"spurious": 5877, |
|
"diagnosis": 1539, |
|
"counterfactuals": 1223, |
|
"investigation": 3024, |
|
"suites": 6046, |
|
"popularity": 4730, |
|
"humanlike": 2703, |
|
"cause": 787, |
|
"economic": 1705, |
|
"political": 4723, |
|
"societal": 5805, |
|
"emphasizes": 1771, |
|
"wild": 6811, |
|
"ecosystem": 1707, |
|
"embedded": 1748, |
|
"involvement": 3029, |
|
"stemming": 5924, |
|
"roadmap": 5505, |
|
"central": 792, |
|
"sentiment": 5646, |
|
"subtask": 6015, |
|
"faces": 2117, |
|
"limits": 3471, |
|
"enterprise": 1857, |
|
"wellknown": 6798, |
|
"materials": 3684, |
|
"ingredients": 2900, |
|
"material": 3683, |
|
"advent": 231, |
|
"convolutional": 1191, |
|
"relationship": 5313, |
|
"competency": 993, |
|
"accelerating": 114, |
|
"acquisition": 162, |
|
"chemical": 842, |
|
"emission": 1765, |
|
"workflow": 6840, |
|
"generalizable": 2357, |
|
"determining": 1515, |
|
"prevalence": 4865, |
|
"retaining": 5454, |
|
"outline": 4440, |
|
"conclude": 1068, |
|
"related": 5309, |
|
"extends": 2086, |
|
"preserve": 4832, |
|
"match": 3680, |
|
"bound": 671, |
|
"stability": 5881, |
|
"retain": 5453, |
|
"reuse": 5471, |
|
"infrastructure": 2899, |
|
"susceptible": 6088, |
|
"represented": 5368, |
|
"approximation": 418, |
|
"collecting": 934, |
|
"groundtruth": 2562, |
|
"annotating": 348, |
|
"annotate": 343, |
|
"pass": 4571, |
|
"math": 3685, |
|
"comprising": 1041, |
|
"exams": 1976, |
|
"commercial": 950, |
|
"maintains": 3644, |
|
"anticipate": 361, |
|
"articles": 440, |
|
"company": 966, |
|
"dense": 1461, |
|
"3rd": 54, |
|
"f1score": 2114, |
|
"lowlevel": 3610, |
|
"cast": 779, |
|
"allow": 308, |
|
"incur": 2847, |
|
"latency": 3350, |
|
"faster": 2156, |
|
"token": 6344, |
|
"tokenlevel": 6347, |
|
"inferencing": 2879, |
|
"kv": 3109, |
|
"overcomes": 4478, |
|
"guarantees": 2570, |
|
"monotonic": 4114, |
|
"eliminating": 1745, |
|
"preceding": 4783, |
|
"works": 6842, |
|
"earlier": 1691, |
|
"obtain": 4345, |
|
"2x": 44, |
|
"speedups": 5872, |
|
"negligible": 4221, |
|
"opt": 4408, |
|
"compatible": 989, |
|
"randomized": 5120, |
|
"accommodate": 122, |
|
"mistakes": 3789, |
|
"arise": 433, |
|
"algorithmically": 295, |
|
"participants": 4560, |
|
"researching": 5402, |
|
"assigned": 464, |
|
"complete": 1002, |
|
"fewer": 2172, |
|
"reported": 5356, |
|
"satisfying": 5540, |
|
"decisions": 1390, |
|
"increases": 2839, |
|
"chain": 796, |
|
"involve": 3027, |
|
"chains": 801, |
|
"allowed": 309, |
|
"transition": 6460, |
|
"costeffective": 1216, |
|
"nonetheless": 4282, |
|
"operators": 4401, |
|
"spend": 5873, |
|
"outcomes": 4439, |
|
"motivated": 4123, |
|
"trust": 6489, |
|
"sending": 5638, |
|
"concern": 1063, |
|
"slightly": 5786, |
|
"pilot": 4684, |
|
"reviews": 5478, |
|
"helpfulness": 2612, |
|
"submitted": 6004, |
|
"conference": 1085, |
|
"tends": 6255, |
|
"avenues": 535, |
|
"enhancements": 1846, |
|
"groundwork": 2564, |
|
"openness": 4387, |
|
"transparency": 6471, |
|
"accountability": 128, |
|
"generators": 2460, |
|
"upheavals": 6597, |
|
"trend": 6481, |
|
"projects": 4946, |
|
"documentation": 1639, |
|
"rlhf": 5502, |
|
"list": 3483, |
|
"share": 5679, |
|
"site": 5775, |
|
"labour": 3122, |
|
"careful": 764, |
|
"rare": 5141, |
|
"fairness": 2140, |
|
"ablation": 95, |
|
"selfconsistency": 5617, |
|
"generations": 2435, |
|
"considerable": 1102, |
|
"sampled": 5533, |
|
"reranking": 5382, |
|
"obtaining": 4347, |
|
"relies": 5328, |
|
"overhead": 4479, |
|
"formalized": 2265, |
|
"theoretically": 6315, |
|
"simulations": 5768, |
|
"assumes": 474, |
|
"blackbox": 654, |
|
"probabilities": 4889, |
|
"inputoutput": 2920, |
|
"trains": 6429, |
|
"enhances": 1847, |
|
"reveals": 5474, |
|
"retrieving": 5469, |
|
"lies": 3445, |
|
"merits": 3730, |
|
"incorporating": 2832, |
|
"enriched": 1852, |
|
"refer": 5278, |
|
"starting": 5895, |
|
"hints": 2648, |
|
"summarizes": 6058, |
|
"adds": 212, |
|
"induction": 2865, |
|
"modelling": 3904, |
|
"phenomena": 4674, |
|
"aspect": 453, |
|
"overlook": 4481, |
|
"documentlevel": 1640, |
|
"coherence": 921, |
|
"necessity": 4207, |
|
"leaderboard": 3363, |
|
"complexities": 1016, |
|
"diseases": 1607, |
|
"pathways": 4581, |
|
"remaining": 5332, |
|
"agi": 247, |
|
"industries": 2869, |
|
"deepmind": 1411, |
|
"anthropic": 358, |
|
"discusses": 1603, |
|
"tie": 6326, |
|
"recommendations": 5254, |
|
"reviewed": 5477, |
|
"obvious": 4349, |
|
"straightforward": 5942, |
|
"supported": 6075, |
|
"flexible": 2239, |
|
"communication": 960, |
|
"feasible": 2161, |
|
"origin": 4435, |
|
"difficulty": 1575, |
|
"calculations": 720, |
|
"maps": 3670, |
|
"referencing": 5282, |
|
"linking": 3481, |
|
"apps": 419, |
|
"deploying": 1471, |
|
"truly": 6488, |
|
"hybrid": 2713, |
|
"drafts": 1673, |
|
"versions": 6748, |
|
"requests": 5372, |
|
"workers": 6839, |
|
"requiring": 5381, |
|
"collaborations": 927, |
|
"status": 5923, |
|
"highdimensional": 2624, |
|
"encodes": 1803, |
|
"demographic": 1428, |
|
"outofdistribution": 4442, |
|
"age": 237, |
|
"wealth": 6789, |
|
"consequently": 1100, |
|
"discussing": 1604, |
|
"identifying": 2729, |
|
"medicine": 3715, |
|
"locating": 3585, |
|
"genetic": 2462, |
|
"breakthroughs": 682, |
|
"view": 6754, |
|
"36": 50, |
|
"opinion": 4402, |
|
"preprocessed": 4814, |
|
"format": 2266, |
|
"inaccessible": 2810, |
|
"barriers": 552, |
|
"wikipedia": 6810, |
|
"library": 3443, |
|
"uncover": 6527, |
|
"scripts": 5584, |
|
"aka": 283, |
|
"replace": 5349, |
|
"discussions": 1606, |
|
"constructed": 1125, |
|
"head": 2602, |
|
"14": 15, |
|
"far": 2154, |
|
"perfect": 4594, |
|
"grasp": 2549, |
|
"abstractions": 108, |
|
"posing": 4736, |
|
"approximately": 417, |
|
"75": 74, |
|
"arises": 434, |
|
"choices": 848, |
|
"caused": 788, |
|
"top2": 6358, |
|
"amplifying": 324, |
|
"recommend": 5251, |
|
"percentage": 4591, |
|
"license": 3444, |
|
"ais": 282, |
|
"proficient": 4929, |
|
"limitation": 3462, |
|
"renders": 5344, |
|
"developments": 1533, |
|
"methodology": 3750, |
|
"includes": 2816, |
|
"constructing": 1126, |
|
"california": 723, |
|
"96": 83, |
|
"driving": 1684, |
|
"fell": 2170, |
|
"fails": 2134, |
|
"examined": 1969, |
|
"sophisticated": 5826, |
|
"trustworthiness": 6490, |
|
"ensuring": 1855, |
|
"myriad": 4165, |
|
"humanannotated": 2691, |
|
"correlate": 1205, |
|
"18": 26, |
|
"enhancement": 1845, |
|
"prevailing": 4864, |
|
"mllm": 3801, |
|
"mllms": 3802, |
|
"benchmarking": 601, |
|
"guidance": 2572, |
|
"closedloop": 879, |
|
"iteration": 3045, |
|
"separate": 5648, |
|
"opensourced": 4394, |
|
"rethinking": 5455, |
|
"play": 4703, |
|
"prominence": 4947, |
|
"indicated": 2855, |
|
"intricate": 2996, |
|
"bidirectionality": 635, |
|
"paths": 4580, |
|
"constrained": 1120, |
|
"universally": 6568, |
|
"counterparts": 1224, |
|
"forecasts": 2256, |
|
"datadriven": 1349, |
|
"weather": 6790, |
|
"postprocessing": 4748, |
|
"tremendous": 6480, |
|
"nwp": 4330, |
|
"reanalysis": 5183, |
|
"era5": 1878, |
|
"forecast": 2254, |
|
"par": 4530, |
|
"highresolution": 2642, |
|
"panguweather": 4493, |
|
"temperature": 6249, |
|
"wind": 6812, |
|
"speed": 5871, |
|
"forecasting": 2255, |
|
"hours": 2657, |
|
"ahead": 249, |
|
"ecmwf": 1703, |
|
"clearly": 874, |
|
"systematic": 6107, |
|
"deficiencies": 1414, |
|
"apart": 362, |
|
"confirm": 1090, |
|
"operational": 4399, |
|
"languagemodel": 3265, |
|
"emotion": 1766, |
|
"ser": 5659, |
|
"humanlabeled": 2700, |
|
"weak": 6785, |
|
"taxonomy": 6229, |
|
"appear": 367, |
|
"prosodic": 5017, |
|
"neurons": 4241, |
|
"ngram": 4265, |
|
"gpu": 2532, |
|
"125m": 11, |
|
"neuron": 4240, |
|
"reserved": 5403, |
|
"act": 163, |
|
"detectors": 1513, |
|
"updates": 6595, |
|
"triggering": 6486, |
|
"adding": 188, |
|
"residual": 5404, |
|
"stream": 5946, |
|
"operate": 4395, |
|
"technical": 6238, |
|
"continue": 1152, |
|
"followup": 2251, |
|
"close": 877, |
|
"mathematics": 3690, |
|
"toxic": 6365, |
|
"figures": 2190, |
|
"predefined": 4787, |
|
"person": 4659, |
|
"sound": 5829, |
|
"characterized": 822, |
|
"encountered": 1810, |
|
"assistants": 471, |
|
"emerges": 1763, |
|
"records": 5261, |
|
"tokenizers": 6346, |
|
"break": 677, |
|
"units": 6566, |
|
"repetitive": 5348, |
|
"treating": 6473, |
|
"consecutive": 1097, |
|
"humancentric": 2693, |
|
"mobile": 3804, |
|
"incorrectly": 2835, |
|
"underscores": 6535, |
|
"nuances": 4310, |
|
"consider": 1101, |
|
"subset": 6011, |
|
"footprint": 2253, |
|
"intermediate": 2984, |
|
"modest": 4105, |
|
"handling": 2592, |
|
"humancreated": 2696, |
|
"covered": 1231, |
|
"caution": 790, |
|
"calibrated": 721, |
|
"speaker": 5846, |
|
"emergence": 1759, |
|
"fidelity": 2180, |
|
"perceived": 4590, |
|
"deterministic": 1516, |
|
"extremely": 2109, |
|
"app": 366, |
|
"decipher": 1385, |
|
"versatility": 6746, |
|
"resilience": 5405, |
|
"emphasize": 1770, |
|
"revolutionized": 5481, |
|
"aligning": 299, |
|
"instabilities": 2932, |
|
"hacking": 2581, |
|
"forgetting": 2257, |
|
"innovations": 2910, |
|
"prevent": 4867, |
|
"mitigates": 3791, |
|
"hierarchical": 2620, |
|
"tens": 6256, |
|
"nonuniform": 4286, |
|
"structural": 5963, |
|
"multistage": 4158, |
|
"adaptability": 175, |
|
"gptj": 2527, |
|
"minimum": 3784, |
|
"total": 6364, |
|
"explainability": 2055, |
|
"true": 6487, |
|
"thirdparty": 6319, |
|
"lowquality": 3611, |
|
"judging": 3058, |
|
"bing": 649, |
|
"trec": 6475, |
|
"pick": 4681, |
|
"rankers": 5134, |
|
"uncertainties": 6523, |
|
"notation": 4292, |
|
"imperfect": 2760, |
|
"describing": 1479, |
|
"closes": 883, |
|
"healthcare": 2605, |
|
"origins": 4437, |
|
"aids": 270, |
|
"grading": 2538, |
|
"modes": 4104, |
|
"deviation": 1535, |
|
"productivity": 4925, |
|
"verifiable": 6739, |
|
"verifiability": 6738, |
|
"author": 501, |
|
"edits": 1711, |
|
"edited": 1709, |
|
"usability": 6600, |
|
"robotics": 5508, |
|
"claims": 853, |
|
"templates": 6250, |
|
"engineered": 1826, |
|
"nearly": 4202, |
|
"unchanged": 6525, |
|
"cosine": 1212, |
|
"averaged": 538, |
|
"suboptimal": 6005, |
|
"tunes": 6496, |
|
"similarities": 5749, |
|
"lines": 3475, |
|
"segmentation": 5603, |
|
"recovery": 5263, |
|
"region": 5295, |
|
"cnn": 887, |
|
"harmful": 2598, |
|
"underrepresented": 6533, |
|
"corrections": 1202, |
|
"incident": 2812, |
|
"frontier": 2307, |
|
"plans": 4699, |
|
"dangerous": 1292, |
|
"informed": 2898, |
|
"respond": 5417, |
|
"detected": 1507, |
|
"prepare": 4813, |
|
"recommending": 5257, |
|
"maintain": 3641, |
|
"establish": 1885, |
|
"developer": 1522, |
|
"claude": 871, |
|
"bloom": 657, |
|
"llama2": 3494, |
|
"restrictions": 5424, |
|
"swift": 6091, |
|
"recognize": 5248, |
|
"artificially": 448, |
|
"instrumental": 2954, |
|
"rag": 5115, |
|
"revolutionizing": 5485, |
|
"witnessed": 6815, |
|
"billions": 645, |
|
"executed": 1988, |
|
"devices": 1536, |
|
"quantization": 5086, |
|
"seamless": 5585, |
|
"implementation": 2762, |
|
"breakthrough": 681, |
|
"opens": 4388, |
|
"possibilities": 4742, |
|
"empowering": 1787, |
|
"pretrained language": 4841, |
|
"current stateoftheart": 1276, |
|
"methods typically": 3760, |
|
"typically rely": 6516, |
|
"semantic features": 5620, |
|
"preprocessing step": 4817, |
|
"models requires": 4067, |
|
"requires additional": 5378, |
|
"introduces additional": 3009, |
|
"generative pretrained": 2452, |
|
"pretrained transformer": 4856, |
|
"radford et": 5109, |
|
"et al": 1893, |
|
"al 2018": 286, |
|
"unlike previous": 6578, |
|
"uses pretrained": 6642, |
|
"deep language": 1403, |
|
"linguistic features": 3478, |
|
"transformer architecture": 6437, |
|
"text corpora": 6280, |
|
"pretraining finetuning": 4862, |
|
"new stateoftheart": 4256, |
|
"stateoftheart result": 5916, |
|
"observe significant": 4341, |
|
"significant increase": 5725, |
|
"sample efficiency": 5532, |
|
"training examples": 6407, |
|
"model trained": 3891, |
|
"trained scratch": 6392, |
|
"trained models": 6390, |
|
"source code": 5831, |
|
"finetuning pretrained": 2230, |
|
"transformer language": 6440, |
|
"language models": 3168, |
|
"widely used": 6807, |
|
"contextual information": 1149, |
|
"achieving stateoftheart": 159, |
|
"stateoftheart results": 5917, |
|
"limited set": 3469, |
|
"long tail": 3594, |
|
"address gap": 201, |
|
"utilize pretrained": 6680, |
|
"language model": 3153, |
|
"transformer gpt": 6439, |
|
"gpt radford": 2498, |
|
"models shown": 4070, |
|
"commonsense knowledge": 958, |
|
"diverse set": 1631, |
|
"automated evaluation": 504, |
|
"model shows": 3880, |
|
"achieves stateoftheart": 155, |
|
"analysis tool": 334, |
|
"learned representations": 3377, |
|
"models large": 3983, |
|
"large language": 3280, |
|
"models produce": 4052, |
|
"nlp tasks": 4272, |
|
"tasks models": 6199, |
|
"models typically": 4089, |
|
"attention mechanisms": 485, |
|
"inductive biases": 2867, |
|
"models lead": 3990, |
|
"reasoning process": 5199, |
|
"model provides": 3875, |
|
"annotated dataset": 347, |
|
"gpt2 bert": 2503, |
|
"question generation": 5097, |
|
"neural network": 4235, |
|
"approaches proposed": 412, |
|
"work propose": 6835, |
|
"network architectures": 4224, |
|
"model generate": 3839, |
|
"generate meaningful": 2378, |
|
"model consisting": 3826, |
|
"gpt2 model": 2508, |
|
"model transformer": 3894, |
|
"transformer encoder": 6438, |
|
"downstream task": 1669, |
|
"question answering": 5095, |
|
"generation text": 2431, |
|
"method produce": 3743, |
|
"produce semantically": 4919, |
|
"assessed performance": 460, |
|
"performance proposed": 4629, |
|
"proposed method": 5009, |
|
"analysis shows": 332, |
|
"particularly powerful": 4569, |
|
"results suggest": 5450, |
|
"overall results": 4474, |
|
"collected wide": 933, |
|
"wide variety": 6804, |
|
"number parameters": 4317, |
|
"reward functions": 5487, |
|
"reinforcement learning": 5301, |
|
"learning methods": 3397, |
|
"latent space": 3352, |
|
"generative model": 2449, |
|
"learning framework": 3389, |
|
"framework natural": 2292, |
|
"natural language": 4175, |
|
"paper propose": 4521, |
|
"largescale language": 3341, |
|
"embedding space": 1751, |
|
"pretrained large": 4845, |
|
"large text": 3331, |
|
"text corpus": 6281, |
|
"finetuned various": 2222, |
|
"various language": 6718, |
|
"language generation": 3141, |
|
"generation understanding": 2432, |
|
"understanding tasks": 6550, |
|
"tasks compared": 6170, |
|
"lowresource language": 3614, |
|
"language understanding": 3257, |
|
"extensive experimental": 2092, |
|
"experimental results": 2036, |
|
"wide range": 6801, |
|
"language tasks": 3255, |
|
"tasks demonstrate": 6172, |
|
"demonstrate effectiveness": 1434, |
|
"achieves new": 152, |
|
"language modeling": 3166, |
|
"model results": 3877, |
|
"deep generative": 1401, |
|
"generative models": 2450, |
|
"largescale pretraining": 3345, |
|
"masked language": 3675, |
|
"word order": 6818, |
|
"model autoregressive": 3818, |
|
"autoregressive language": 524, |
|
"models pretrained": 4049, |
|
"models bert": 3924, |
|
"understanding nlu": 6547, |
|
"nlu tasks": 4278, |
|
"models gpt": 3966, |
|
"generation nlg": 2420, |
|
"text generation": 6288, |
|
"generation pretrained": 2421, |
|
"outperforms bert": 4454, |
|
"downstream nlu": 1667, |
|
"tasks challenging": 6168, |
|
"training data": 6397, |
|
"class imbalance": 855, |
|
"work present": 6833, |
|
"present data": 4824, |
|
"simple method": 5758, |
|
"augment training": 496, |
|
"gpt2 generate": 2504, |
|
"types generated": 6511, |
|
"data used": 1345, |
|
"dataset train": 1362, |
|
"method leads": 3741, |
|
"f1 score": 2112, |
|
"strong baseline": 5955, |
|
"state art": 5899, |
|
"previous best": 4870, |
|
"best results": 622, |
|
"paraphrase generation": 4552, |
|
"generation using": 2434, |
|
"using pretrained": 6665, |
|
"large scale": 3330, |
|
"scale pretrained": 5546, |
|
"approach various": 405, |
|
"various natural": 6722, |
|
"openais gpt2": 4379, |
|
"consistent text": 1111, |
|
"paper leverage": 4516, |
|
"generation capability": 2408, |
|
"generate paraphrases": 2380, |
|
"labelled data": 3117, |
|
"data augmentation": 1295, |
|
"downstream tasks": 1670, |
|
"paraphrases generated": 4554, |
|
"generated model": 2393, |
|
"task performance": 6154, |
|
"research area": 5384, |
|
"recent studies": 5221, |
|
"studies shown": 5977, |
|
"word embeddings": 6817, |
|
"language processing": 3248, |
|
"processing tasks": 4912, |
|
"unlike existing": 6577, |
|
"existing work": 2016, |
|
"work evaluate": 6827, |
|
"previously unseen": 4877, |
|
"model achieves": 3814, |
|
"top5 accuracy": 6360, |
|
"challenging task": 813, |
|
"furthermore use": 2324, |
|
"neural language": 4229, |
|
"models paper": 4042, |
|
"previous research": 4872, |
|
"generative language": 2446, |
|
"different types": 1571, |
|
"significant improvement": 5723, |
|
"significant risk": 5728, |
|
"effective policy": 1720, |
|
"sequencetosequence tasks": 5656, |
|
"questionanswer pairs": 5100, |
|
"applying large": 388, |
|
"large pretrained": 3326, |
|
"generation models": 2418, |
|
"models outperform": 4041, |
|
"strong baselines": 5956, |
|
"metrics human": 3769, |
|
"human raters": 2684, |
|
"case study": 775, |
|
"course months": 1228, |
|
"automatically generated": 517, |
|
"research community": 5385, |
|
"recent advances": 5212, |
|
"remains challenging": 5336, |
|
"generated text": 2396, |
|
"outperform existing": 4446, |
|
"controllable generation": 1170, |
|
"generation methods": 2416, |
|
"automatic human": 508, |
|
"human evaluations": 2669, |
|
"pretrained lm": 4853, |
|
"smaller size": 5799, |
|
"work highlights": 6830, |
|
"small lms": 5792, |
|
"approach consists": 392, |
|
"learning objective": 3402, |
|
"order solve": 4427, |
|
"solve problem": 5816, |
|
"current solutions": 1274, |
|
"imitation learning": 2749, |
|
"intent detection": 2970, |
|
"enhance performance": 1843, |
|
"propose method": 4991, |
|
"model gpt2": 3844, |
|
"context prompt": 1144, |
|
"fewshot learning": 2175, |
|
"bert roberta": 616, |
|
"qa systems": 5066, |
|
"questionanswering qa": 5102, |
|
"strong performance": 5958, |
|
"performance zeroshot": 4645, |
|
"order magnitude": 4424, |
|
"magnitude smaller": 3635, |
|
"175 billion": 22, |
|
"billion parameters": 644, |
|
"inputs outputs": 2923, |
|
"answer question": 353, |
|
"question types": 5098, |
|
"outside training": 4467, |
|
"training setup": 6422, |
|
"offering insights": 4356, |
|
"taskoriented dialog": 6163, |
|
"dialog systems": 1545, |
|
"labeling cost": 3115, |
|
"major challenge": 3647, |
|
"different tasks": 1569, |
|
"labeled data": 3112, |
|
"data recently": 1328, |
|
"prompting methods": 4971, |
|
"shown promising": 5707, |
|
"promising results": 4954, |
|
"paper proposes": 4527, |
|
"taskspecific instructions": 6227, |
|
"dialog state": 1541, |
|
"state tracking": 5900, |
|
"tracking natural": 6369, |
|
"solve tasks": 5819, |
|
"unified framework": 6559, |
|
"extensive experiments": 2094, |
|
"experiments conducted": 2043, |
|
"empirical results": 1776, |
|
"results demonstrate": 5435, |
|
"demonstrate proposed": 1445, |
|
"approach consistently": 391, |
|
"empirical study": 1778, |
|
"study gpt3": 5985, |
|
"answering questions": 356, |
|
"require external": 5374, |
|
"external knowledge": 2098, |
|
"knowledge present": 3095, |
|
"existing methods": 2013, |
|
"knowledge external": 3084, |
|
"approach lead": 398, |
|
"address challenge": 198, |
|
"challenge propose": 804, |
|
"simple effective": 5755, |
|
"effective method": 1719, |
|
"image captions": 2738, |
|
"knowledge retrieval": 3098, |
|
"instead using": 2937, |
|
"previous work": 4874, |
|
"incontext examples": 2826, |
|
"tasks using": 6221, |
|
"foundation models": 2279, |
|
"models education": 3944, |
|
"al 2021": 289, |
|
"opportunities risks": 4405, |
|
"models represent": 4065, |
|
"paradigm shift": 4532, |
|
"models trained": 4086, |
|
"bert gpt3": 614, |
|
"computer vision": 1056, |
|
"computational approaches": 1046, |
|
"models likely": 3998, |
|
"introduce new": 3002, |
|
"language prompts": 3254, |
|
"models currently": 3937, |
|
"datasets associated": 1366, |
|
"prompting approach": 4967, |
|
"scaling model": 5555, |
|
"model size": 3884, |
|
"room improvement": 5516, |
|
"human annotators": 2664, |
|
"proposed approach": 5006, |
|
"scaling law": 5553, |
|
"recent advancement": 5210, |
|
"pretrained models": 4855, |
|
"learning training": 3414, |
|
"contrastive learning": 1157, |
|
"various downstream": 6716, |
|
"shows great": 5713, |
|
"shows significant": 5715, |
|
"significant improvements": 5724, |
|
"model performance": 3867, |
|
"size model": 5779, |
|
"model capacity": 3823, |
|
"sequence length": 5652, |
|
"batch size": 579, |
|
"finally discuss": 2199, |
|
"broader impacts": 699, |
|
"human feedback": 2673, |
|
"allows model": 314, |
|
"setting task": 5673, |
|
"task performed": 6155, |
|
"train models": 6382, |
|
"task using": 6160, |
|
"learning optimize": 3403, |
|
"human evaluation": 2668, |
|
"models collect": 3932, |
|
"train evaluate": 6378, |
|
"evaluate models": 1912, |
|
"best model": 621, |
|
"gpt3 using": 2517, |
|
"rejection sampling": 5308, |
|
"reward model": 5489, |
|
"trained predict": 6391, |
|
"human preferences": 2683, |
|
"models investigate": 3979, |
|
"current large": 1271, |
|
"models significantly": 4071, |
|
"scaling language": 5551, |
|
"number training": 4320, |
|
"training tokens": 6427, |
|
"test hypothesis": 6267, |
|
"significantly outperforms": 5740, |
|
"gpt3 175b": 2514, |
|
"range downstream": 5124, |
|
"evaluation tasks": 1950, |
|
"models conversational": 3936, |
|
"new perspectives": 4255, |
|
"systems paper": 6115, |
|
"paper investigate": 4514, |
|
"incontext learning": 2827, |
|
"models address": 3912, |
|
"address problem": 206, |
|
"information extraction": 2885, |
|
"gpt3 generative": 2515, |
|
"transformer model": 6443, |
|
"limited number": 3468, |
|
"number samples": 4318, |
|
"results highlight": 5438, |
|
"highlight potential": 2631, |
|
"deep learning": 1404, |
|
"learning based": 3384, |
|
"control flow": 1167, |
|
"open source": 4372, |
|
"source framework": 5832, |
|
"learning rl": 3408, |
|
"users easily": 6636, |
|
"social media": 5803, |
|
"use pretrained": 6617, |
|
"good results": 2487, |
|
"work approach": 6826, |
|
"named entities": 4167, |
|
"text classification": 6277, |
|
"capabilities generative": 730, |
|
"sufficiently large": 6037, |
|
"second finetune": 5597, |
|
"autonomous agents": 522, |
|
"agents paper": 244, |
|
"paper analyze": 4500, |
|
"learning algorithms": 3381, |
|
"policy optimization": 4720, |
|
"optimization ppo": 4413, |
|
"learning algorithm": 3380, |
|
"sparse rewards": 5841, |
|
"models including": 3976, |
|
"propose novel": 4996, |
|
"synthetic data": 6106, |
|
"biomedical entities": 653, |
|
"structured data": 5967, |
|
"generate coherent": 2373, |
|
"new datasets": 4245, |
|
"human experts": 2672, |
|
"human evaluators": 2671, |
|
"summarization task": 6054, |
|
"models help": 3970, |
|
"model human": 3847, |
|
"larger models": 3338, |
|
"despite having": 1502, |
|
"suggest large": 6039, |
|
"large models": 3324, |
|
"scale supervision": 5547, |
|
"machine learning": 3620, |
|
"learning systems": 3410, |
|
"tasks difficult": 6173, |
|
"training datasets": 6404, |
|
"novel recipe": 4303, |
|
"recipe generation": 5241, |
|
"growing using": 2567, |
|
"generation problem": 2424, |
|
"field natural": 2184, |
|
"generate realistic": 2382, |
|
"learning models": 3400, |
|
"gpt2 large": 2507, |
|
"knowledge transfer": 3102, |
|
"remarkable performance": 5339, |
|
"performance gains": 4615, |
|
"models gpt3": 3968, |
|
"massive amounts": 3677, |
|
"amounts data": 322, |
|
"unlabeled training": 6572, |
|
"data paper": 1324, |
|
"pretrained generative": 4839, |
|
"need large": 4211, |
|
"large volume": 3333, |
|
"input space": 2918, |
|
"image classification": 2739, |
|
"classification benchmarks": 860, |
|
"twostage method": 6506, |
|
"al 2020": 288, |
|
"language inference": 3147, |
|
"zeroshot setting": 6878, |
|
"quality model": 5079, |
|
"evaluate performance": 1913, |
|
"zeroshot performance": 6877, |
|
"semantically similar": 5628, |
|
"ground truth": 2558, |
|
"widely applied": 6806, |
|
"business scenarios": 715, |
|
"low resource": 3607, |
|
"innovative approach": 2912, |
|
"machine translation": 3627, |
|
"recently large": 5233, |
|
"models models": 4030, |
|
"models evaluated": 3947, |
|
"2022 shared": 36, |
|
"shared task": 5681, |
|
"root mean": 5518, |
|
"models recent": 4061, |
|
"training everlarger": 6406, |
|
"models substantially": 4077, |
|
"substantially improved": 6014, |
|
"models make": 4025, |
|
"prohibitively expensive": 4943, |
|
"study efficient": 5983, |
|
"simple general": 5757, |
|
"tasks time": 6219, |
|
"efficiency performance": 1732, |
|
"neural machine": 4231, |
|
"generalizes language": 2366, |
|
"language pairs": 3246, |
|
"improve performance": 2791, |
|
"performance downstream": 4611, |
|
"learning multiple": 3401, |
|
"learning rate": 3405, |
|
"improves performance": 2802, |
|
"code used": 904, |
|
"facilitate research": 2121, |
|
"transformer networks": 6445, |
|
"work aims": 6825, |
|
"retrievalbased methods": 5463, |
|
"vision tasks": 6759, |
|
"paper present": 4518, |
|
"enables model": 1795, |
|
"overall accuracy": 4471, |
|
"model using": 3897, |
|
"recent research": 5220, |
|
"additional context": 192, |
|
"answering qa": 355, |
|
"performance stateoftheart": 4635, |
|
"high quality": 2623, |
|
"knowledge bases": 3081, |
|
"incomplete knowledge": 2822, |
|
"learns generate": 3419, |
|
"knowledge response": 3097, |
|
"generated gpt3": 2387, |
|
"consistent performance": 1110, |
|
"benchmarks including": 604, |
|
"model training": 3892, |
|
"generated models": 2394, |
|
"orders magnitude": 4430, |
|
"methods word": 3763, |
|
"future directions": 2328, |
|
"stateoftheart performance": 5914, |
|
"numerous natural": 4328, |
|
"music paper": 4164, |
|
"paper argue": 4501, |
|
"business process": 714, |
|
"models handle": 3969, |
|
"tasks like": 6195, |
|
"decision making": 1387, |
|
"models tackle": 4081, |
|
"unique challenges": 6564, |
|
"data scarcity": 1331, |
|
"domain specific": 1653, |
|
"privacy concerns": 4887, |
|
"semiparametric language": 5633, |
|
"models generally": 3960, |
|
"huge number": 2659, |
|
"number model": 4315, |
|
"model parameters": 3866, |
|
"knowledge solving": 3099, |
|
"world knowledge": 6847, |
|
"novel semiparametric": 4304, |
|
"model architecture": 3816, |
|
"types knowledge": 6512, |
|
"knowledge augmentation": 3080, |
|
"texttotext model": 6308, |
|
"input output": 2916, |
|
"mixtureofexperts moe": 3799, |
|
"model knowledge": 3852, |
|
"performance unseen": 4639, |
|
"unseen tasks": 6587, |
|
"tasks evaluating": 6174, |
|
"770m parameters": 76, |
|
"models lms": 4024, |
|
"large margin": 3323, |
|
"emergent abilities": 1761, |
|
"abilities smaller": 86, |
|
"smaller model": 5797, |
|
"model scale": 3878, |
|
"models leveraging": 3992, |
|
"models recently": 4062, |
|
"processing nlp": 4909, |
|
"nlp domain": 4270, |
|
"text summarization": 6299, |
|
"transformer models": 6444, |
|
"performance compared": 4606, |
|
"recurrent neural": 5267, |
|
"network models": 4226, |
|
"term memory": 6258, |
|
"attention mechanism": 484, |
|
"causal language": 784, |
|
"model downstream": 3830, |
|
"task generating": 6148, |
|
"semiconductor industry": 5631, |
|
"models generative": 3964, |
|
"task particular": 6153, |
|
"15b parameters": 18, |
|
"parameters outperforms": 4545, |
|
"pretrained bert": 4836, |
|
"furthermore introduce": 2323, |
|
"evaluation metric": 1944, |
|
"transformerbased large": 6450, |
|
"models llms": 4001, |
|
"llms provide": 3556, |
|
"tasks largescale": 6194, |
|
"types attacks": 6510, |
|
"prompt engineering": 4961, |
|
"model llm": 3856, |
|
"compared baselines": 978, |
|
"falls short": 2145, |
|
"current state": 1275, |
|
"used transfer": 6625, |
|
"llms llms": 3548, |
|
"llms directly": 3529, |
|
"training finetuning": 6408, |
|
"computational costs": 1048, |
|
"real world": 5166, |
|
"propose framework": 4989, |
|
"models particular": 4044, |
|
"visual elements": 6763, |
|
"textual information": 6311, |
|
"new variants": 4260, |
|
"stepbystep reasoning": 5928, |
|
"reasoning large": 5193, |
|
"models improved": 3975, |
|
"reasoning steps": 5204, |
|
"automatic evaluation": 506, |
|
"extend previous": 2083, |
|
"evaluation metrics": 1945, |
|
"reasoning errors": 5192, |
|
"commonly used": 956, |
|
"reasoning datasets": 5190, |
|
"human annotated": 2661, |
|
"set tasks": 5669, |
|
"tasks require": 6209, |
|
"reasoning skills": 5202, |
|
"consistently outperform": 1113, |
|
"outperform baseline": 4445, |
|
"propose benchmark": 4987, |
|
"benchmark dataset": 596, |
|
"dataset consisting": 1357, |
|
"stateoftheart pretrained": 5915, |
|
"like gpt3": 3454, |
|
"significantly improves": 5736, |
|
"improves accuracy": 2799, |
|
"chatgpt model": 832, |
|
"advanced understanding": 223, |
|
"understanding complex": 6540, |
|
"coding tasks": 914, |
|
"like chatgpt": 3451, |
|
"chatgpt offer": 833, |
|
"offer novel": 4354, |
|
"novel tool": 4306, |
|
"tool use": 6350, |
|
"diverse tasks": 1633, |
|
"model tasks": 3888, |
|
"chatgpts ability": 838, |
|
"future work": 2332, |
|
"data science": 1332, |
|
"models llm": 4000, |
|
"openais chatgpt": 4378, |
|
"1000 times": 6, |
|
"times smaller": 6337, |
|
"models capabilities": 3927, |
|
"importance derive": 2776, |
|
"test cases": 6266, |
|
"using linear": 6657, |
|
"linear regression": 3474, |
|
"recent years": 5224, |
|
"years pretrained": 6861, |
|
"achieving new": 158, |
|
"models rely": 4064, |
|
"annotated data": 346, |
|
"data available": 1296, |
|
"available data": 531, |
|
"specialized domains": 5852, |
|
"lowresource languages": 3615, |
|
"ai research": 260, |
|
"learning techniques": 3412, |
|
"models research": 4068, |
|
"research directions": 5389, |
|
"evaluate impact": 1907, |
|
"models downstream": 3942, |
|
"downstream nlp": 1665, |
|
"tasks specifically": 6212, |
|
"context using": 1145, |
|
"using text": 6670, |
|
"data results": 1330, |
|
"results indicate": 5441, |
|
"domains tasks": 1658, |
|
"models code": 3931, |
|
"large lms": 3322, |
|
"trained massive": 6389, |
|
"used generate": 6623, |
|
"generate code": 2372, |
|
"evaluate lms": 1909, |
|
"task called": 6144, |
|
"code generation": 894, |
|
"generation task": 2429, |
|
"capability generating": 743, |
|
"generating functionally": 2401, |
|
"functionally correct": 2316, |
|
"correct code": 1201, |
|
"code propose": 899, |
|
"approach called": 390, |
|
"solve task": 5818, |
|
"highquality dataset": 2640, |
|
"carefully curated": 766, |
|
"evaluation shows": 1948, |
|
"highly effective": 2637, |
|
"strong security": 5959, |
|
"significantly boosted": 5733, |
|
"functional correctness": 2313, |
|
"stateoftheart language": 5910, |
|
"model gpt3": 3845, |
|
"documents providing": 1642, |
|
"semantic information": 5621, |
|
"models able": 3908, |
|
"able predict": 102, |
|
"information provided": 2890, |
|
"nlp models": 4271, |
|
"learning large": 3395, |
|
"task generalization": 6147, |
|
"instruction tuning": 2941, |
|
"learning human": 3390, |
|
"various tasks": 6727, |
|
"improves zeroshot": 2804, |
|
"performance pretrained": 4627, |
|
"evaluate tasks": 1916, |
|
"particular demonstrate": 4564, |
|
"data annotation": 1294, |
|
"use case": 6605, |
|
"capabilities natural": 737, |
|
"generation tasks": 2430, |
|
"end paper": 1816, |
|
"paper examine": 4507, |
|
"zeroshot text": 6879, |
|
"model finetuned": 3837, |
|
"manually annotated": 3666, |
|
"models compared": 3933, |
|
"test sets": 6270, |
|
"languages english": 3269, |
|
"finetuned model": 2219, |
|
"english model": 1840, |
|
"limitations chatgpt": 3464, |
|
"manual annotation": 3664, |
|
"paper outlines": 4517, |
|
"particular discuss": 4565, |
|
"research objectives": 5399, |
|
"study investigates": 5987, |
|
"realworld setting": 5180, |
|
"goal determine": 2483, |
|
"job posting": 3052, |
|
"traditional models": 6375, |
|
"models like": 3994, |
|
"stateoftheart deep": 5908, |
|
"llms used": 3576, |
|
"zeroshot classification": 6873, |
|
"detailed analysis": 1504, |
|
"impact different": 2754, |
|
"models performance": 4046, |
|
"performance results": 4631, |
|
"supervised approach": 6067, |
|
"approach furthermore": 396, |
|
"reasoning model": 5196, |
|
"affect models": 235, |
|
"language interface": 3149, |
|
"data exploration": 1304, |
|
"powered large": 4763, |
|
"insights data": 2926, |
|
"using chatgpt": 6645, |
|
"artificial intelligence": 446, |
|
"intelligence ai": 2964, |
|
"ai generative": 253, |
|
"chatgpt produce": 834, |
|
"realistic human": 5168, |
|
"human interactions": 2677, |
|
"paper investigates": 4515, |
|
"ai large": 255, |
|
"evaluation text": 1951, |
|
"complex problem": 1008, |
|
"methods like": 3756, |
|
"propose new": 4995, |
|
"new evaluation": 4247, |
|
"evaluation framework": 1934, |
|
"framework based": 2287, |
|
"comprehensive evaluation": 1035, |
|
"propose model": 4992, |
|
"based input": 562, |
|
"input context": 2914, |
|
"integrate multiple": 2957, |
|
"evaluation results": 1946, |
|
"summarization model": 6051, |
|
"highly competitive": 2636, |
|
"texttoimage diffusion": 6306, |
|
"diffusion models": 1578, |
|
"generative capabilities": 2445, |
|
"models suggest": 4079, |
|
"data knowledge": 1308, |
|
"tasks investigate": 6185, |
|
"key idea": 3067, |
|
"models ability": 3907, |
|
"given text": 2474, |
|
"text description": 6284, |
|
"stable diffusion": 5883, |
|
"models knowledge": 3980, |
|
"zeroshot abilities": 6869, |
|
"perform competitively": 4597, |
|
"achieve stateoftheart": 145, |
|
"generative pretraining": 2457, |
|
"visual foundation": 6764, |
|
"based findings": 559, |
|
"using gpt4": 6648, |
|
"better human": 624, |
|
"metrics bleu": 3767, |
|
"using large": 6653, |
|
"new tasks": 4258, |
|
"assess quality": 458, |
|
"tasks text": 6215, |
|
"dialogue generation": 1547, |
|
"spearman correlation": 5849, |
|
"outperforming previous": 4451, |
|
"previous methods": 4871, |
|
"methods large": 3755, |
|
"shed light": 5684, |
|
"publicly available": 5048, |
|
"available code": 530, |
|
"knowledge dataset": 3082, |
|
"address issue": 202, |
|
"issue introduce": 3034, |
|
"llm large": 3503, |
|
"language modelbased": 3165, |
|
"exploration process": 2066, |
|
"selects appropriate": 5613, |
|
"meaningful coherent": 3701, |
|
"enabling users": 1799, |
|
"valuable insights": 6695, |
|
"various applications": 6714, |
|
"search engines": 5589, |
|
"engines recommendation": 1835, |
|
"recommendation systems": 5253, |
|
"llms demonstrated": 3524, |
|
"demonstrated impressive": 1450, |
|
"impressive capabilities": 2786, |
|
"range tasks": 5128, |
|
"tasks work": 6222, |
|
"llms able": 3512, |
|
"given textual": 2475, |
|
"user intent": 6630, |
|
"prompting llms": 4970, |
|
"given new": 2470, |
|
"pretrained llm": 4851, |
|
"embedding model": 1750, |
|
"strong generalization": 5957, |
|
"applications evaluate": 374, |
|
"available datasets": 532, |
|
"compared existing": 979, |
|
"project page": 4945, |
|
"prior work": 4885, |
|
"finetuning large": 2225, |
|
"llms using": 3577, |
|
"models achieve": 3910, |
|
"zeroshot capabilities": 6870, |
|
"use gpt4": 6609, |
|
"data llm": 1316, |
|
"llm finetuning": 3500, |
|
"early experiments": 1694, |
|
"llama models": 3493, |
|
"english chinese": 1838, |
|
"previous stateoftheart": 4873, |
|
"stateoftheart models": 5913, |
|
"generated using": 2397, |
|
"better instruction": 625, |
|
"data evaluation": 1303, |
|
"recently significant": 5239, |
|
"significant public": 5727, |
|
"conversational models": 1183, |
|
"scarcity comprehensive": 5559, |
|
"study examine": 5984, |
|
"quantity quality": 5085, |
|
"multiturn conversations": 4162, |
|
"various models": 6721, |
|
"models using": 4092, |
|
"evaluation set": 1947, |
|
"realworld scenarios": 5179, |
|
"models furthermore": 3958, |
|
"training inference": 6409, |
|
"make model": 3651, |
|
"model data": 3827, |
|
"data code": 1297, |
|
"code publicly": 901, |
|
"comparative study": 971, |
|
"instruction data": 2939, |
|
"instructiontuning large": 2951, |
|
"area research": 430, |
|
"research field": 5391, |
|
"encouraging results": 1813, |
|
"benefits terms": 610, |
|
"training costs": 6396, |
|
"base model": 555, |
|
"model experimental": 3834, |
|
"training dataset": 6403, |
|
"conclusions paper": 1071, |
|
"training large": 6410, |
|
"models especially": 3946, |
|
"dataset model": 1359, |
|
"model code": 3825, |
|
"code released": 903, |
|
"optimization algorithm": 4411, |
|
"models different": 3941, |
|
"different scales": 1567, |
|
"qualitative analysis": 5071, |
|
"analysis large": 327, |
|
"labels data": 3119, |
|
"large datasets": 3275, |
|
"readily available": 5161, |
|
"taskspecific models": 6228, |
|
"models study": 4075, |
|
"explored use": 2071, |
|
"use large": 6611, |
|
"training taskspecific": 6425, |
|
"tasks finetuning": 6177, |
|
"learning using": 3415, |
|
"using llms": 6658, |
|
"llms support": 3571, |
|
"finetuned language": 2215, |
|
"generalization unseen": 2361, |
|
"tasks including": 6183, |
|
"semantic role": 5623, |
|
"finetuned models": 2220, |
|
"outperform previous": 4447, |
|
"models tasks": 4082, |
|
"tasks addition": 6166, |
|
"parameter efficient": 4537, |
|
"efficient finetuning": 1734, |
|
"model performances": 3868, |
|
"strong zeroshot": 5960, |
|
"propose simple": 4999, |
|
"method applies": 3736, |
|
"applies large": 383, |
|
"built neural": 712, |
|
"neural models": 4234, |
|
"benchmark datasets": 597, |
|
"llm generate": 3501, |
|
"retrieval module": 5459, |
|
"semantic knowledge": 5622, |
|
"variety tasks": 6712, |
|
"tasks searching": 6211, |
|
"propose natural": 4993, |
|
"knowledge large": 3089, |
|
"llms contain": 3522, |
|
"tasks particular": 6202, |
|
"large corpus": 3273, |
|
"text data": 6283, |
|
"boosts performance": 666, |
|
"performance tasks": 4636, |
|
"identify key": 2728, |
|
"llms text": 3572, |
|
"provide strong": 5027, |
|
"learning tasks": 3411, |
|
"learning ml": 3398, |
|
"widespread adoption": 6809, |
|
"time consuming": 6331, |
|
"hard understand": 2594, |
|
"paper aim": 4496, |
|
"aim bridge": 273, |
|
"bridge gap": 687, |
|
"gap machine": 2343, |
|
"machine intelligence": 3619, |
|
"human knowledge": 2679, |
|
"novel framework": 4302, |
|
"leverages stateoftheart": 3436, |
|
"stateoftheart llms": 5912, |
|
"llms develop": 3528, |
|
"novel tasks": 4305, |
|
"capability llms": 748, |
|
"reasoning solving": 5203, |
|
"large number": 3325, |
|
"approaches based": 408, |
|
"additionally present": 196, |
|
"present novel": 4826, |
|
"novel data": 4300, |
|
"compare performance": 975, |
|
"logical reasoning": 3590, |
|
"knowledge graphs": 3086, |
|
"models reasoning": 4060, |
|
"graphs kgs": 2547, |
|
"task requires": 6156, |
|
"current approaches": 1269, |
|
"subpar performance": 6007, |
|
"performance complex": 4607, |
|
"representations paper": 5364, |
|
"experiments demonstrate": 2044, |
|
"approach outperforms": 401, |
|
"outperforms stateoftheart": 4460, |
|
"standard benchmark": 5888, |
|
"performance approach": 4602, |
|
"underlying llm": 6531, |
|
"advancements llms": 226, |
|
"work presents": 6834, |
|
"new direction": 4246, |
|
"paves way": 4585, |
|
"way future": 6781, |
|
"future research": 2331, |
|
"training llms": 6415, |
|
"demonstrated remarkable": 1453, |
|
"program synthesis": 4931, |
|
"quality learned": 5078, |
|
"neural scaling": 4238, |
|
"scaling laws": 5554, |
|
"data compute": 1300, |
|
"key components": 3066, |
|
"components model": 1022, |
|
"model architectures": 3817, |
|
"mixture distribution": 3796, |
|
"languages model": 3270, |
|
"conduct comprehensive": 1079, |
|
"empirical experiments": 1775, |
|
"parameters training": 4547, |
|
"beam search": 583, |
|
"llms shown": 3565, |
|
"shown impressive": 5703, |
|
"impressive performance": 2787, |
|
"performance general": 4616, |
|
"effort propose": 1738, |
|
"llm api": 3498, |
|
"form natural": 2259, |
|
"task descriptions": 6146, |
|
"knowledge distillation": 3083, |
|
"distillation large": 1617, |
|
"models introduce": 3978, |
|
"llms generate": 3537, |
|
"generate accurate": 2371, |
|
"techniques create": 6243, |
|
"student model": 5973, |
|
"model accuracy": 3812, |
|
"data collected": 1298, |
|
"allowing model": 311, |
|
"model used": 3895, |
|
"ai models": 258, |
|
"academic performance": 111, |
|
"models demonstrated": 3939, |
|
"domains including": 1656, |
|
"customer service": 1282, |
|
"tasks suggesting": 6213, |
|
"potential applications": 4752, |
|
"lead highly": 3362, |
|
"expand range": 2020, |
|
"models improve": 3974, |
|
"emergent capabilities": 1762, |
|
"llms understand": 3574, |
|
"evaluating llms": 1925, |
|
"prediction large": 4795, |
|
"exceptional capabilities": 1984, |
|
"tasks zeroshot": 6224, |
|
"zeroshot fewshot": 6874, |
|
"based previous": 569, |
|
"collaborative filtering": 929, |
|
"paper conduct": 4503, |
|
"investigate various": 3020, |
|
"various llms": 6720, |
|
"different sizes": 1568, |
|
"parameters evaluate": 4543, |
|
"comprehensive analysis": 1033, |
|
"models access": 3909, |
|
"finetuning llms": 2228, |
|
"achieve comparable": 141, |
|
"better performance": 626, |
|
"performance small": 4632, |
|
"small fraction": 5789, |
|
"fraction training": 2282, |
|
"human intelligence": 2675, |
|
"ai systems": 262, |
|
"systems substantial": 6119, |
|
"problems systems": 4898, |
|
"evaluation benchmark": 1929, |
|
"generalization abilities": 2359, |
|
"benchmark machine": 598, |
|
"openais gpt4": 4380, |
|
"development ai": 1526, |
|
"evaluation systems": 1949, |
|
"zero fewshot": 6866, |
|
"need scale": 4213, |
|
"models new": 4034, |
|
"paper explore": 4508, |
|
"domain adaptation": 1649, |
|
"adaptation data": 177, |
|
"classification using": 864, |
|
"descriptions large": 1482, |
|
"parameterefficient finetuning": 4541, |
|
"models results": 4069, |
|
"results approaches": 5431, |
|
"approaches effective": 409, |
|
"lowresource settings": 3616, |
|
"al 2022": 290, |
|
"grand challenges": 2543, |
|
"grand challenge": 2542, |
|
"significant progress": 5726, |
|
"significant room": 5729, |
|
"medical domain": 3714, |
|
"domain finetuning": 1650, |
|
"prompting strategies": 4973, |
|
"validate efficacy": 6689, |
|
"models realworld": 4058, |
|
"rapid progress": 5139, |
|
"large generative": 3278, |
|
"development process": 1532, |
|
"data collection": 1299, |
|
"instruction finetuning": 2940, |
|
"serve guide": 5663, |
|
"development large": 1528, |
|
"learning language": 3393, |
|
"solve complex": 5815, |
|
"complex tasks": 1013, |
|
"effective efficient": 1718, |
|
"reasoning abilities": 5187, |
|
"inference stage": 2876, |
|
"llms effectively": 3531, |
|
"tasks extensive": 6176, |
|
"datasets method": 1369, |
|
"method achieves": 3735, |
|
"performance standard": 4634, |
|
"terms accuracy": 6262, |
|
"demonstrate exceptional": 1435, |
|
"summarization tasks": 6055, |
|
"automatic metrics": 510, |
|
"issue propose": 3038, |
|
"summarization capabilities": 6049, |
|
"achieves similar": 154, |
|
"superior performance": 6064, |
|
"performance gpt35": 4617, |
|
"fewshot settings": 2178, |
|
"small models": 5793, |
|
"llms potentially": 3554, |
|
"language descriptions": 3140, |
|
"method uses": 3748, |
|
"gpt models": 2497, |
|
"models perform": 4045, |
|
"use different": 6607, |
|
"structured text": 5968, |
|
"generate plausible": 2381, |
|
"small language": 5790, |
|
"learning capabilities": 3385, |
|
"tasks furthermore": 6178, |
|
"fewshot prompting": 2177, |
|
"prompting llm": 4969, |
|
"using smaller": 6669, |
|
"produce final": 4917, |
|
"performance llms": 4622, |
|
"need extensive": 4210, |
|
"finally showcase": 2200, |
|
"inference time": 2877, |
|
"covid19 pandemic": 1234, |
|
"easily accessible": 1698, |
|
"stateoftheart approaches": 5907, |
|
"recent large": 5216, |
|
"llms gpt4": 3538, |
|
"uses gpt4": 6641, |
|
"correct answer": 1200, |
|
"different languages": 1559, |
|
"instructions examples": 2946, |
|
"new approach": 4243, |
|
"uses gpt2": 6640, |
|
"results showed": 5449, |
|
"size context": 5778, |
|
"like bert": 3450, |
|
"bert gpt2": 613, |
|
"gpt2 t5": 2510, |
|
"finetuned large": 2217, |
|
"shown effective": 5701, |
|
"input text": 2919, |
|
"models finetuned": 3954, |
|
"different text": 1570, |
|
"text perturbations": 6294, |
|
"general language": 2352, |
|
"understanding evaluation": 6542, |
|
"evaluation glue": 1935, |
|
"glue benchmark": 2480, |
|
"pretrained finetuned": 4837, |
|
"models exhibit": 3950, |
|
"overall study": 4475, |
|
"study provides": 5990, |
|
"provides valuable": 5032, |
|
"transformerbased models": 6456, |
|
"incontext demonstration": 2825, |
|
"cross entropy": 1252, |
|
"llms use": 3575, |
|
"selecting best": 5609, |
|
"challenging model": 811, |
|
"method based": 3737, |
|
"example language": 1973, |
|
"models training": 4087, |
|
"evaluate method": 1910, |
|
"performance variety": 4640, |
|
"variety llms": 6709, |
|
"models excel": 3949, |
|
"controlling models": 1174, |
|
"models finetuning": 3955, |
|
"finetuning reinforcement": 2231, |
|
"requires model": 5379, |
|
"model access": 3811, |
|
"model decoding": 3828, |
|
"decoding time": 1395, |
|
"brings significant": 695, |
|
"outperforms competitive": 4455, |
|
"baseline methods": 572, |
|
"methods including": 3754, |
|
"dataset diverse": 1358, |
|
"practical applications": 4779, |
|
"able perform": 101, |
|
"used different": 6622, |
|
"models capable": 3928, |
|
"models understanding": 4090, |
|
"able achieve": 99, |
|
"performance different": 4609, |
|
"remains challenge": 5335, |
|
"understanding generation": 6544, |
|
"user experience": 6629, |
|
"paper aims": 4497, |
|
"aims address": 278, |
|
"recommender systems": 5256, |
|
"llms foundation": 3536, |
|
"models reason": 4059, |
|
"great potential": 2552, |
|
"models providing": 4055, |
|
"stepping stone": 5930, |
|
"new user": 4259, |
|
"models fewshot": 3952, |
|
"realworld tasks": 5181, |
|
"tasks language": 6189, |
|
"llms excel": 3533, |
|
"timeseries data": 6339, |
|
"evaluate capabilities": 1905, |
|
"mental health": 3727, |
|
"given context": 2468, |
|
"different ways": 1572, |
|
"experiments using": 2048, |
|
"models generate": 3961, |
|
"ability large": 89, |
|
"traditional methods": 6374, |
|
"different domains": 1557, |
|
"improve quality": 2792, |
|
"prompts llms": 4976, |
|
"llms struggle": 3569, |
|
"software engineering": 5808, |
|
"engineering tasks": 1830, |
|
"family large": 2150, |
|
"serve foundation": 5662, |
|
"diverse domains": 1629, |
|
"test case": 6265, |
|
"performed using": 4650, |
|
"analyze chatgpts": 338, |
|
"chatgpt does": 829, |
|
"does perform": 1644, |
|
"response detailed": 5419, |
|
"incorrect answers": 2834, |
|
"tasks improving": 6182, |
|
"improving accuracy": 2806, |
|
"information training": 2892, |
|
"alternative approach": 316, |
|
"approach use": 402, |
|
"specific domain": 5854, |
|
"llm performance": 3504, |
|
"readability scores": 5158, |
|
"gpt35 gpt4": 2520, |
|
"findings suggest": 2206, |
|
"specific domains": 5855, |
|
"semantic search": 5624, |
|
"tasks research": 6210, |
|
"research explore": 5390, |
|
"generative ai": 2438, |
|
"ai education": 252, |
|
"prompting techniques": 4974, |
|
"engineers using": 1833, |
|
"text embedding": 6286, |
|
"using generative": 6646, |
|
"study demonstrate": 5982, |
|
"efficiently accurately": 1736, |
|
"synthesis visual": 6101, |
|
"visual programming": 6766, |
|
"models hold": 3971, |
|
"hold great": 2652, |
|
"great promise": 2553, |
|
"models automatically": 3918, |
|
"automatically generate": 516, |
|
"programming tasks": 4934, |
|
"like gpt4": 3455, |
|
"reasoning propose": 5201, |
|
"extensive empirical": 2090, |
|
"empirical evaluation": 1774, |
|
"information unstructured": 2893, |
|
"unstructured text": 6590, |
|
"critical task": 1250, |
|
"research large": 5395, |
|
"potential accelerate": 4750, |
|
"supervised learning": 6069, |
|
"human annotations": 2663, |
|
"modern llms": 4103, |
|
"results method": 5443, |
|
"accuracy various": 136, |
|
"text span": 6298, |
|
"paving way": 4587, |
|
"resourceconstrained scenarios": 5411, |
|
"research direction": 5388, |
|
"guided generation": 2575, |
|
"generation large": 2410, |
|
"llms successfully": 3570, |
|
"vast amounts": 6734, |
|
"supervision paper": 6072, |
|
"llm trained": 3505, |
|
"outperforms existing": 4456, |
|
"methods based": 3753, |
|
"based generative": 560, |
|
"generative adversarial": 2437, |
|
"introduce concept": 3001, |
|
"conduct indepth": 1081, |
|
"indepth analysis": 2852, |
|
"learning complex": 3386, |
|
"research focused": 5392, |
|
"smaller models": 5798, |
|
"outputs generated": 4465, |
|
"generated large": 2389, |
|
"large foundation": 3276, |
|
"tend learn": 6253, |
|
"address challenges": 200, |
|
"model weights": 3898, |
|
"parameter model": 4539, |
|
"model learns": 3855, |
|
"instructiontuned models": 2949, |
|
"reasoning benchmarks": 5188, |
|
"benchmarks like": 605, |
|
"bigbench hard": 638, |
|
"competitive performance": 998, |
|
"promising direction": 4953, |
|
"llms like": 3545, |
|
"radiology reports": 5114, |
|
"data training": 1343, |
|
"leverages largescale": 3433, |
|
"better zeroshot": 630, |
|
"participating systems": 4562, |
|
"2023 workshop": 40, |
|
"models powerful": 4048, |
|
"tasks ranging": 6207, |
|
"mathematical reasoning": 3689, |
|
"present paper": 4827, |
|
"paper address": 4495, |
|
"finetuning data": 2224, |
|
"experiments models": 2046, |
|
"models offer": 4035, |
|
"human behavior": 2665, |
|
"model behavior": 3821, |
|
"demonstrate finetuning": 1436, |
|
"multiple tasks": 4156, |
|
"cognitive psychology": 919, |
|
"crosslingual transfer": 1255, |
|
"named entity": 4168, |
|
"entity recognition": 1864, |
|
"recognition ner": 5247, |
|
"timeconsuming expensive": 6334, |
|
"multilingual large": 4138, |
|
"finetuned specific": 2221, |
|
"specific task": 5858, |
|
"task language": 6149, |
|
"high accuracy": 2622, |
|
"translation models": 6467, |
|
"models used": 4091, |
|
"data target": 1339, |
|
"target language": 6141, |
|
"training set": 6421, |
|
"set test": 5670, |
|
"test set": 6269, |
|
"paper compares": 4502, |
|
"methods perform": 3757, |
|
"french german": 2303, |
|
"data languages": 1311, |
|
"methods achieve": 3752, |
|
"achieve similar": 143, |
|
"similar performance": 5747, |
|
"better results": 627, |
|
"multilingual models": 4140, |
|
"existing approaches": 2004, |
|
"fail provide": 2133, |
|
"knowledge llms": 3094, |
|
"llms work": 3579, |
|
"models specifically": 4074, |
|
"llms exhibit": 3534, |
|
"code data": 891, |
|
"adversarial training": 233, |
|
"common practice": 952, |
|
"sensitive information": 5641, |
|
"generate text": 2384, |
|
"models learn": 3991, |
|
"code available": 889, |
|
"new large": 4251, |
|
"significantly smaller": 5744, |
|
"competing models": 995, |
|
"parameters trained": 4546, |
|
"using selection": 6668, |
|
"quality data": 5077, |
|
"data web": 1346, |
|
"pass1 accuracy": 4573, |
|
"model finetuning": 3838, |
|
"conversational ai": 1181, |
|
"conversational agents": 1180, |
|
"ai agents": 251, |
|
"personal data": 4661, |
|
"like real": 3457, |
|
"paper explores": 4509, |
|
"human users": 2689, |
|
"spurious correlations": 5878, |
|
"models visual": 4097, |
|
"generate diverse": 2375, |
|
"drawing inspiration": 1679, |
|
"test suites": 6271, |
|
"case chatgpt": 774, |
|
"generating humanlike": 2404, |
|
"offering users": 4357, |
|
"ethical issues": 1900, |
|
"better understand": 628, |
|
"development deployment": 1527, |
|
"central approach": 793, |
|
"sentiment analysis": 5647, |
|
"annotated corpora": 345, |
|
"specifically designed": 5861, |
|
"data necessary": 1321, |
|
"processing techniques": 4913, |
|
"recent advancements": 5211, |
|
"performance natural": 4625, |
|
"language pattern": 3247, |
|
"existing opensource": 2015, |
|
"opensource llms": 4392, |
|
"analysis tasks": 333, |
|
"dataset publicly": 1361, |
|
"neural networks": 4237, |
|
"convolutional neural": 1192, |
|
"models openais": 4038, |
|
"reading comprehension": 5163, |
|
"demonstrate possibility": 1443, |
|
"transfer learning": 6433, |
|
"minimal human": 3781, |
|
"human supervision": 2687, |
|
"domain knowledge": 1651, |
|
"content analysis": 1136, |
|
"qualitative research": 5072, |
|
"text documents": 6285, |
|
"ai tools": 266, |
|
"range natural": 5125, |
|
"reasoning tasks": 5205, |
|
"explore use": 2069, |
|
"use llms": 6615, |
|
"reduce time": 5271, |
|
"data set": 1334, |
|
"conduct empirical": 1080, |
|
"additionally demonstrate": 195, |
|
"vs human": 6775, |
|
"pretrained llms": 4852, |
|
"demonstrating strong": 1458, |
|
"results various": 5452, |
|
"retrieval language": 5458, |
|
"selfattention mechanism": 5615, |
|
"models extended": 3951, |
|
"groundtruth labels": 2563, |
|
"algorithm sampling": 293, |
|
"active learning": 167, |
|
"semantic similarity": 5625, |
|
"leads significant": 3369, |
|
"accuracy training": 134, |
|
"target domains": 6140, |
|
"math word": 3686, |
|
"word problems": 6819, |
|
"dataset comprising": 1356, |
|
"dataset aims": 1352, |
|
"aims provide": 281, |
|
"benchmark tool": 600, |
|
"popular llms": 4729, |
|
"llms including": 3540, |
|
"findings reveal": 2205, |
|
"robustness model": 5511, |
|
"llms arithmetic": 3515, |
|
"arithmetic reasoning": 436, |
|
"reasoning capabilities": 5189, |
|
"models relation": 4063, |
|
"crucial task": 1260, |
|
"task natural": 6150, |
|
"aims identify": 280, |
|
"plays vital": 4710, |
|
"vital role": 6770, |
|
"news articles": 4264, |
|
"paper describes": 4504, |
|
"unstructured data": 6589, |
|
"models framework": 3957, |
|
"data given": 1307, |
|
"given test": 2473, |
|
"recently shown": 5238, |
|
"human level": 2680, |
|
"level performance": 3427, |
|
"tasks ability": 6165, |
|
"ability models": 93, |
|
"perform complex": 4598, |
|
"complex visual": 1015, |
|
"process propose": 4903, |
|
"propose address": 4986, |
|
"inspiration human": 2929, |
|
"reasoning problems": 5198, |
|
"end introduce": 1815, |
|
"llm inference": 3502, |
|
"progress various": 4939, |
|
"incur high": 2848, |
|
"computation cost": 1044, |
|
"reduce computational": 5270, |
|
"computational cost": 1047, |
|
"practical application": 4778, |
|
"designed work": 1494, |
|
"eliminating need": 1746, |
|
"computational resources": 1050, |
|
"inference speedups": 2875, |
|
"13 billion": 13, |
|
"algorithmically generated": 296, |
|
"tasks involved": 6187, |
|
"information presented": 2889, |
|
"accuracy using": 135, |
|
"using traditional": 6672, |
|
"information llm": 2887, |
|
"need spend": 4214, |
|
"does require": 1645, |
|
"develop general": 1519, |
|
"study investigate": 5986, |
|
"investigate use": 3019, |
|
"generated human": 2388, |
|
"learning tools": 3413, |
|
"resource constraints": 5409, |
|
"text generators": 6292, |
|
"conversational interfaces": 1182, |
|
"trend large": 6482, |
|
"release openais": 5319, |
|
"model text": 3889, |
|
"main contribution": 3638, |
|
"contribution paper": 1163, |
|
"human annotation": 2662, |
|
"architecture training": 425, |
|
"remarkable capabilities": 5338, |
|
"study llms": 5988, |
|
"llms additional": 3513, |
|
"important area": 2778, |
|
"supervised stateoftheart": 6070, |
|
"points f1": 4716, |
|
"ablation studies": 96, |
|
"generation quality": 2426, |
|
"novel approach": 4298, |
|
"analyze performance": 339, |
|
"tasks based": 6167, |
|
"inputoutput examples": 2921, |
|
"dense retrievers": 1462, |
|
"examples llms": 1975, |
|
"model based": 3820, |
|
"feedback evaluate": 2168, |
|
"evaluate quality": 1915, |
|
"framework significantly": 2295, |
|
"significantly enhances": 5734, |
|
"tasks training": 6220, |
|
"analysis reveals": 331, |
|
"model improves": 3848, |
|
"varying sizes": 6731, |
|
"paper presents": 4519, |
|
"framework automatic": 2286, |
|
"specific tasks": 5859, |
|
"highquality prompts": 2641, |
|
"learning zeroshot": 3416, |
|
"zeroshot learning": 6876, |
|
"instructions derived": 2945, |
|
"form new": 2261, |
|
"dataset zeroshot": 1364, |
|
"demonstrate method": 1442, |
|
"method able": 3733, |
|
"boost accuracy": 663, |
|
"language modelling": 3167, |
|
"existing evaluation": 2007, |
|
"evaluation benchmarks": 1930, |
|
"benchmarks primarily": 606, |
|
"primarily focus": 4879, |
|
"gap propose": 2344, |
|
"translation generation": 6466, |
|
"models based": 3921, |
|
"llms results": 3563, |
|
"performance evaluation": 4613, |
|
"evaluation large": 1938, |
|
"approaches study": 413, |
|
"capabilities large": 732, |
|
"address issues": 205, |
|
"automatically extracting": 515, |
|
"work investigate": 6832, |
|
"effectiveness different": 1726, |
|
"tasks involve": 6186, |
|
"performance various": 4641, |
|
"discuss future": 1601, |
|
"remaining challenges": 5333, |
|
"artificial general": 443, |
|
"general intelligence": 2350, |
|
"intelligence agi": 2963, |
|
"systems perform": 6117, |
|
"ai paper": 259, |
|
"paper discusses": 4505, |
|
"systems employ": 6113, |
|
"knowledge sources": 3100, |
|
"information various": 2895, |
|
"human responses": 2686, |
|
"current capabilities": 1270, |
|
"scenarios enhance": 5562, |
|
"usage generative": 6602, |
|
"paper introduces": 4512, |
|
"multimodal llms": 4147, |
|
"impressive ability": 2785, |
|
"ability solve": 94, |
|
"effectively solve": 1723, |
|
"tasks llms": 6198, |
|
"model multimodal": 3858, |
|
"effectively use": 1724, |
|
"learning approaches": 3383, |
|
"literature search": 3488, |
|
"specific information": 5856, |
|
"using tools": 6671, |
|
"tools finally": 6352, |
|
"perspective future": 4665, |
|
"recent breakthroughs": 5213, |
|
"breakthroughs large": 683, |
|
"models chatgpt": 3930, |
|
"open dataset": 4370, |
|
"gap available": 2341, |
|
"existing datasets": 2006, |
|
"past years": 4578, |
|
"available visual": 534, |
|
"time series": 6332, |
|
"preprocessed data": 4815, |
|
"given recent": 2471, |
|
"large dataset": 3274, |
|
"enable researchers": 1791, |
|
"data preprocessing": 1325, |
|
"available github": 533, |
|
"llms knowledge": 3542, |
|
"llms paper": 3551, |
|
"benchmark consists": 595, |
|
"evaluation method": 1943, |
|
"knowledge llm": 3093, |
|
"llms far": 3535, |
|
"information retrieval": 2891, |
|
"retrieval systems": 5460, |
|
"accuracy factual": 133, |
|
"framework designed": 2290, |
|
"designed facilitate": 1493, |
|
"facilitate development": 2120, |
|
"overall performance": 4472, |
|
"opensource code": 4390, |
|
"capabilities various": 739, |
|
"various nlp": 6724, |
|
"previous works": 4875, |
|
"works shown": 6843, |
|
"shown models": 5705, |
|
"posing challenges": 4737, |
|
"paper focus": 4510, |
|
"questions demonstrate": 5105, |
|
"different benchmarks": 1556, |
|
"uncertain prediction": 6522, |
|
"different models": 1560, |
|
"models benchmarks": 3923, |
|
"models open": 4036, |
|
"open ais": 4369, |
|
"information present": 2888, |
|
"data limitation": 1315, |
|
"recent developments": 5215, |
|
"proposes method": 5014, |
|
"models answer": 3916, |
|
"context information": 1141, |
|
"generating answers": 2400, |
|
"using gpt": 6647, |
|
"gpt3 model": 2516, |
|
"model achieved": 3813, |
|
"context format": 1140, |
|
"tasks summarization": 6214, |
|
"paper introduce": 4511, |
|
"introduce novel": 3004, |
|
"machinegenerated text": 3629, |
|
"finetune model": 2212, |
|
"new method": 4252, |
|
"method evaluation": 3739, |
|
"metrics correlate": 3768, |
|
"consistently outperforms": 1114, |
|
"models finally": 3953, |
|
"finally compare": 2198, |
|
"using metric": 6660, |
|
"despite great": 1501, |
|
"multimodal large": 4143, |
|
"models mllms": 4028, |
|
"training evaluation": 6405, |
|
"data generation": 1306, |
|
"generation model": 2417, |
|
"dataset training": 1363, |
|
"enhance model": 1842, |
|
"compared previous": 981, |
|
"shows better": 5712, |
|
"quality correctness": 5076, |
|
"dataset based": 1353, |
|
"results quality": 5448, |
|
"generate highquality": 2376, |
|
"highquality data": 2639, |
|
"given data": 2469, |
|
"data type": 1344, |
|
"prompt design": 4960, |
|
"generation results": 2428, |
|
"results previous": 5446, |
|
"generated data": 2386, |
|
"symbolic knowledge": 6093, |
|
"kgs play": 3073, |
|
"gained prominence": 2335, |
|
"models match": 4026, |
|
"reasoning processes": 5200, |
|
"evaluation language": 1936, |
|
"models varying": 4094, |
|
"sizes capabilities": 5782, |
|
"benchmarks encompass": 603, |
|
"novel evaluation": 4301, |
|
"evaluation various": 1952, |
|
"shows models": 5714, |
|
"factual information": 2130, |
|
"kgs remains": 3074, |
|
"proposed evaluation": 5007, |
|
"metrics reliable": 3770, |
|
"numerical weather": 4324, |
|
"weather prediction": 6791, |
|
"prediction nwp": 4800, |
|
"data recent": 1327, |
|
"highresolution model": 2643, |
|
"wind speed": 6813, |
|
"spatial resolution": 5844, |
|
"models larger": 3988, |
|
"results confirm": 5434, |
|
"humanlabeled data": 2701, |
|
"speech datasets": 5867, |
|
"unlabeled data": 6571, |
|
"automatic speech": 511, |
|
"speech recognition": 5869, |
|
"baseline models": 573, |
|
"models lightweight": 3993, |
|
"single gpu": 5773, |
|
"family models": 2153, |
|
"large collection": 3272, |
|
"best knowledge": 620, |
|
"data smaller": 1336, |
|
"models operate": 4040, |
|
"technical report": 6239, |
|
"transformerbased language": 6447, |
|
"10 million": 3, |
|
"million parameter": 3773, |
|
"model produce": 3872, |
|
"produce coherent": 4915, |
|
"coherent english": 923, |
|
"billion parameter": 642, |
|
"performance close": 4605, |
|
"learning process": 3404, |
|
"compared traditional": 982, |
|
"web data": 6794, |
|
"common sense": 954, |
|
"model named": 3859, |
|
"llms complex": 3521, |
|
"complex reasoning": 1009, |
|
"larger llms": 3336, |
|
"including hallucinations": 2818, |
|
"better understanding": 629, |
|
"data large": 1312, |
|
"data models": 1317, |
|
"break text": 678, |
|
"text smaller": 6297, |
|
"recent works": 5223, |
|
"employ llms": 1781, |
|
"increasingly large": 2843, |
|
"llms demonstrate": 3523, |
|
"generation capabilities": 2407, |
|
"individual tasks": 2859, |
|
"realworld applications": 5177, |
|
"memory footprint": 3723, |
|
"maintaining improving": 3643, |
|
"improving performance": 2807, |
|
"comparison existing": 987, |
|
"methods reveals": 3759, |
|
"decent performance": 1384, |
|
"nlg tasks": 4268, |
|
"tasks question": 6205, |
|
"summarization classification": 6050, |
|
"score output": 5578, |
|
"output models": 4463, |
|
"models usually": 4093, |
|
"llms increasingly": 3541, |
|
"increasingly popular": 2844, |
|
"techniques including": 6244, |
|
"llms capable": 3517, |
|
"capable handling": 751, |
|
"lack systematic": 3127, |
|
"systematic evaluation": 6109, |
|
"evaluate language": 1908, |
|
"tasks languages": 6190, |
|
"recent development": 5214, |
|
"prediction models": 4799, |
|
"performance traditional": 4638, |
|
"models work": 4098, |
|
"models appear": 3917, |
|
"model embeddings": 3832, |
|
"mobile applications": 3805, |
|
"issues paper": 3040, |
|
"approach utilizes": 404, |
|
"public datasets": 5043, |
|
"intricate patterns": 2997, |
|
"various scenarios": 6726, |
|
"potential llms": 4758, |
|
"llms revolutionized": 3564, |
|
"revolutionized natural": 5482, |
|
"aligning models": 300, |
|
"models human": 3972, |
|
"human values": 2690, |
|
"significant challenge": 5721, |
|
"reward hacking": 5488, |
|
"experimental analysis": 2035, |
|
"public proprietary": 5044, |
|
"proposed methods": 5011, |
|
"explanation large": 2058, |
|
"structural information": 5964, |
|
"parameters gptneo": 4544, |
|
"gptneo gptj": 2530, |
|
"models propose": 4053, |
|
"points previous": 4717, |
|
"accurately predict": 139, |
|
"does scale": 1646, |
|
"approach improving": 397, |
|
"models largescale": 3989, |
|
"models effective": 3945, |
|
"various domains": 6715, |
|
"models specialized": 4073, |
|
"internet data": 2988, |
|
"pretraining large": 4863, |
|
"vertical domains": 6750, |
|
"text generated": 6287, |
|
"humans ai": 2705, |
|
"failure modes": 2136, |
|
"capabilities introduce": 731, |
|
"systematic approach": 6108, |
|
"understanding reasoning": 6549, |
|
"iterative process": 3047, |
|
"applications llms": 375, |
|
"llms recently": 3558, |
|
"recently popular": 5237, |
|
"way obtain": 6783, |
|
"introduces new": 3010, |
|
"new information": 4250, |
|
"commonsense reasoning": 959, |
|
"visionlanguage models": 6761, |
|
"shown remarkable": 5710, |
|
"broad range": 697, |
|
"classification tasks": 863, |
|
"words characters": 6823, |
|
"cosine similarity": 1213, |
|
"computational overhead": 1049, |
|
"easily implemented": 1699, |
|
"implemented lines": 2767, |
|
"lines code": 3476, |
|
"outperforms baselines": 4453, |
|
"models datasets": 3938, |
|
"learning fewshot": 3387, |
|
"deep neural": 1407, |
|
"specifically propose": 5862, |
|
"propose strategy": 5002, |
|
"model called": 3822, |
|
"using number": 6664, |
|
"number examples": 4314, |
|
"incident response": 2813, |
|
"models comprehensive": 3935, |
|
"industries including": 2870, |
|
"use cases": 6606, |
|
"cases ai": 777, |
|
"models available": 3920, |
|
"opensource models": 4393, |
|
"enabling llms": 1797, |
|
"data offering": 1322, |
|
"datasets significant": 1371, |
|
"applications study": 380, |
|
"teacher model": 6232, |
|
"model order": 3860, |
|
"interface users": 2982, |
|
"study aims": 5979, |
|
"generative artificial": 2442, |
|
"generation rag": 2427, |
|
"field artificial": 2182, |
|
"progress recent": 4938, |
|
"years especially": 6857, |
|
"powerful large": 4770, |
|
"llms based": 3516, |
|
"llms openais": 3550, |
|
"concerns regarding": 1067, |
|
"article presents": 439, |
|
"approach llm": 400, |
|
"future llms": 2330, |
|
"billions parameters": 646, |
|
"code model": 896, |
|
"insights training": 2927, |
|
"training pipeline": 6419, |
|
"test results": 6268, |
|
"methods typically rely": 3761, |
|
"generative pretrained transformer": 2453, |
|
"radford et al": 5110, |
|
"et al 2018": 1894, |
|
"new stateoftheart result": 4257, |
|
"transformer language models": 6442, |
|
"pretrained language model": 4842, |
|
"pretrained transformer gpt": 4857, |
|
"gpt radford et": 2499, |
|
"models large language": 3984, |
|
"large language models": 3285, |
|
"language models produce": 3228, |
|
"nlp tasks models": 4273, |
|
"tasks models typically": 6200, |
|
"language model provides": 3161, |
|
"language model trained": 3163, |
|
"performance proposed method": 4630, |
|
"framework natural language": 2293, |
|
"large text corpus": 3332, |
|
"language generation understanding": 3145, |
|
"generation understanding tasks": 2433, |
|
"language understanding tasks": 3262, |
|
"extensive experimental results": 2093, |
|
"achieves new stateoftheart": 153, |
|
"deep generative models": 1402, |
|
"model autoregressive language": 3819, |
|
"autoregressive language model": 525, |
|
"language models pretrained": 3227, |
|
"language models bert": 3173, |
|
"natural language understanding": 4191, |
|
"language understanding nlu": 3261, |
|
"autoregressive language models": 526, |
|
"natural language generation": 4177, |
|
"language generation nlg": 3143, |
|
"downstream nlu tasks": 1668, |
|
"training data used": 6402, |
|
"pretrained language models": 4844, |
|
"language models large": 3191, |
|
"various natural language": 6723, |
|
"natural language tasks": 4190, |
|
"paraphrases generated model": 4555, |
|
"natural language processing": 4183, |
|
"language processing tasks": 3253, |
|
"neural language models": 4230, |
|
"language models paper": 3226, |
|
"generative language models": 2448, |
|
"large pretrained transformer": 3329, |
|
"automatic human evaluations": 509, |
|
"language model gpt2": 3158, |
|
"order magnitude smaller": 4425, |
|
"175 billion parameters": 23, |
|
"shown promising results": 5708, |
|
"dialog state tracking": 1542, |
|
"state tracking natural": 5901, |
|
"tracking natural language": 6370, |
|
"empirical results demonstrate": 1777, |
|
"address challenge propose": 199, |
|
"simple effective method": 5756, |
|
"et al 2021": 1897, |
|
"natural language prompts": 4189, |
|
"various downstream tasks": 6717, |
|
"train evaluate models": 6379, |
|
"language models investigate": 3188, |
|
"transformer language model": 6441, |
|
"current large language": 1272, |
|
"scaling language models": 5552, |
|
"large pretrained language": 3327, |
|
"systems paper investigate": 6116, |
|
"models address problem": 3913, |
|
"results highlight potential": 5439, |
|
"deep learning based": 1405, |
|
"open source framework": 4373, |
|
"reinforcement learning rl": 5305, |
|
"use pretrained language": 6618, |
|
"language models shown": 3232, |
|
"policy optimization ppo": 4721, |
|
"language generation models": 3142, |
|
"generation models including": 2419, |
|
"paper propose novel": 4524, |
|
"machine learning systems": 3624, |
|
"field natural language": 2185, |
|
"deep learning models": 1406, |
|
"large pretrained models": 3328, |
|
"massive amounts data": 3678, |
|
"unlabeled training data": 6573, |
|
"training data paper": 6401, |
|
"pretrained generative models": 4840, |
|
"need large volume": 4212, |
|
"et al 2020": 1896, |
|
"natural language inference": 4181, |
|
"recently large language": 5234, |
|
"2022 shared task": 37, |
|
"neural machine translation": 4232, |
|
"machine learning models": 3623, |
|
"question answering qa": 5096, |
|
"numerous natural language": 4329, |
|
"semiparametric language models": 5635, |
|
"number model parameters": 4316, |
|
"semiparametric language model": 5634, |
|
"language models lms": 3219, |
|
"generation pretrained language": 2422, |
|
"language models recently": 3231, |
|
"language processing nlp": 3250, |
|
"processing nlp domain": 4910, |
|
"neural network models": 4236, |
|
"causal language models": 786, |
|
"transformerbased large language": 6451, |
|
"language models llms": 3198, |
|
"large language model": 3281, |
|
"language model llm": 3160, |
|
"paper propose framework": 4522, |
|
"reasoning large language": 5194, |
|
"language models improved": 3187, |
|
"diverse set tasks": 1632, |
|
"significantly improves accuracy": 5737, |
|
"like chatgpt offer": 3452, |
|
"language models llm": 3197, |
|
"language models recent": 3230, |
|
"recent years pretrained": 5228, |
|
"downstream nlp tasks": 1666, |
|
"language models trained": 3238, |
|
"models large lms": 3987, |
|
"generating functionally correct": 2402, |
|
"functionally correct code": 2317, |
|
"code propose novel": 900, |
|
"language model gpt3": 3159, |
|
"learning large language": 3396, |
|
"reinforcement learning human": 5302, |
|
"learning human feedback": 3391, |
|
"significantly improves zeroshot": 5738, |
|
"capabilities natural language": 738, |
|
"language generation tasks": 3144, |
|
"zeroshot text classification": 6880, |
|
"language model finetuned": 3156, |
|
"stateoftheart deep learning": 5909, |
|
"powered large language": 4764, |
|
"artificial intelligence ai": 447, |
|
"ai large language": 256, |
|
"paper propose new": 4523, |
|
"new evaluation framework": 4248, |
|
"comprehensive evaluation framework": 1036, |
|
"achieve stateoftheart results": 146, |
|
"visual foundation models": 6765, |
|
"using large language": 6654, |
|
"publicly available code": 5049, |
|
"address issue introduce": 203, |
|
"search engines recommendation": 5590, |
|
"engines recommendation systems": 1836, |
|
"models llms demonstrated": 4004, |
|
"llms demonstrated impressive": 3525, |
|
"wide range tasks": 6802, |
|
"tasks work propose": 6223, |
|
"publicly available datasets": 5051, |
|
"finetuning large language": 2226, |
|
"models llms using": 4023, |
|
"training data evaluation": 6398, |
|
"language models like": 3196, |
|
"models like gpt3": 3996, |
|
"code publicly available": 902, |
|
"instructiontuning large language": 2952, |
|
"model experimental results": 3835, |
|
"training large language": 6411, |
|
"largescale language model": 3342, |
|
"analysis large language": 328, |
|
"use large language": 6612, |
|
"finetuned language models": 2216, |
|
"outperform previous stateoftheart": 4448, |
|
"parameter efficient finetuning": 4538, |
|
"work propose simple": 6837, |
|
"propose simple method": 5001, |
|
"applies large language": 384, |
|
"propose natural language": 4994, |
|
"knowledge large language": 3090, |
|
"machine learning ml": 3622, |
|
"aim bridge gap": 274, |
|
"bridge gap machine": 688, |
|
"language models reasoning": 3229, |
|
"knowledge graphs kgs": 3087, |
|
"representations paper propose": 5365, |
|
"experiments demonstrate proposed": 2045, |
|
"llms demonstrated remarkable": 3527, |
|
"neural scaling laws": 4239, |
|
"causal language modeling": 785, |
|
"models llms shown": 4018, |
|
"llms shown impressive": 3566, |
|
"shown impressive performance": 5704, |
|
"training data llm": 6400, |
|
"form natural language": 2260, |
|
"distillation large language": 1618, |
|
"prediction large language": 4796, |
|
"performance zeroshot fewshot": 4646, |
|
"descriptions large language": 1483, |
|
"et al 2022": 1898, |
|
"significant room improvement": 5730, |
|
"large generative language": 3279, |
|
"generative language model": 2447, |
|
"learning language models": 3394, |
|
"address issue propose": 204, |
|
"experimental results demonstrate": 2037, |
|
"zeroshot fewshot settings": 6875, |
|
"natural language descriptions": 4176, |
|
"small language models": 5791, |
|
"language models improve": 3186, |
|
"fewshot learning capabilities": 2176, |
|
"recent large language": 5217, |
|
"models llms gpt4": 4011, |
|
"models like bert": 3995, |
|
"processing nlp tasks": 4911, |
|
"models bert gpt2": 3925, |
|
"general language understanding": 2353, |
|
"language understanding evaluation": 3258, |
|
"understanding evaluation glue": 6543, |
|
"pretrained finetuned language": 4838, |
|
"study provides valuable": 5991, |
|
"provides valuable insights": 5033, |
|
"models llms use": 4022, |
|
"models training data": 4088, |
|
"text generation tasks": 6289, |
|
"language models excel": 3178, |
|
"language models finetuning": 3180, |
|
"finetuning reinforcement learning": 2232, |
|
"development large language": 1529, |
|
"language understanding generation": 3260, |
|
"paper aims address": 4498, |
|
"aims address gap": 279, |
|
"language models gpt3": 3185, |
|
"language models generate": 3182, |
|
"ability large language": 90, |
|
"models llms generate": 4010, |
|
"software engineering tasks": 5809, |
|
"family large language": 2151, |
|
"reinforcement learning techniques": 5306, |
|
"chatgpt does perform": 830, |
|
"language models generative": 3184, |
|
"generative ai education": 2439, |
|
"models automatically generate": 3919, |
|
"generative models like": 2451, |
|
"models like gpt4": 3997, |
|
"extensive empirical evaluation": 2091, |
|
"information unstructured text": 2894, |
|
"research large language": 5396, |
|
"experimental results method": 2038, |
|
"guided generation large": 2576, |
|
"generation large language": 2411, |
|
"models llms successfully": 4021, |
|
"outperforms existing methods": 4458, |
|
"conduct indepth analysis": 1082, |
|
"large foundation models": 3277, |
|
"models llms like": 4012, |
|
"llms like chatgpt": 3546, |
|
"named entity recognition": 4169, |
|
"entity recognition ner": 1865, |
|
"multilingual large language": 4139, |
|
"data target language": 1340, |
|
"achieve similar performance": 144, |
|
"models downstream tasks": 3943, |
|
"language models learn": 3195, |
|
"performance natural language": 4626, |
|
"machine learning techniques": 3625, |
|
"convolutional neural network": 1193, |
|
"language models openais": 3225, |
|
"range natural language": 5126, |
|
"publicly available data": 5050, |
|
"math word problems": 3687, |
|
"task natural language": 6151, |
|
"plays vital role": 4711, |
|
"training data given": 6399, |
|
"drawing inspiration human": 1680, |
|
"text generation using": 6290, |
|
"paper propose simple": 4526, |
|
"propose simple effective": 5000, |
|
"machine learning tools": 3626, |
|
"language models exhibit": 3179, |
|
"language model text": 3162, |
|
"model text generation": 3890, |
|
"demonstrated remarkable capabilities": 1454, |
|
"range tasks including": 5129, |
|
"models llms exhibit": 4009, |
|
"code generation tasks": 895, |
|
"propose novel framework": 4998, |
|
"existing evaluation benchmarks": 2008, |
|
"evaluation benchmarks primarily": 1931, |
|
"benchmarks primarily focus": 607, |
|
"evaluation large language": 1939, |
|
"capabilities large language": 733, |
|
"language models address": 3170, |
|
"code data available": 892, |
|
"artificial general intelligence": 444, |
|
"general intelligence agi": 2351, |
|
"ai systems perform": 263, |
|
"language models models": 3221, |
|
"machine learning approaches": 3621, |
|
"breakthroughs large language": 684, |
|
"language models chatgpt": 3175, |
|
"llms knowledge graphs": 3543, |
|
"pretrained large language": 4847, |
|
"capabilities various nlp": 740, |
|
"various nlp tasks": 6725, |
|
"works shown models": 6844, |
|
"different models benchmarks": 1561, |
|
"language models open": 3223, |
|
"models open ais": 4037, |
|
"introduce novel approach": 3005, |
|
"finetune model generate": 2213, |
|
"multimodal large language": 4144, |
|
"language models mllms": 3220, |
|
"model training evaluation": 3893, |
|
"graphs kgs play": 2548, |
|
"evaluation language models": 1937, |
|
"language models varying": 3241, |
|
"models varying sizes": 4095, |
|
"varying sizes capabilities": 6732, |
|
"numerical weather prediction": 4325, |
|
"weather prediction nwp": 6792, |
|
"automatic speech recognition": 512, |
|
"models pretrained large": 4050, |
|
"pretrained large datasets": 4846, |
|
"data smaller models": 1337, |
|
"transformerbased language models": 6449, |
|
"produce coherent english": 4916, |
|
"billion parameter model": 643, |
|
"complex reasoning tasks": 1010, |
|
"data large language": 1313, |
|
"break text smaller": 679, |
|
"models llms demonstrate": 4003, |
|
"understanding generation capabilities": 6545, |
|
"tasks question answering": 6206, |
|
"lack systematic evaluation": 3128, |
|
"models llms revolutionized": 4017, |
|
"revolutionized natural language": 5483, |
|
"aligning models human": 301, |
|
"models human values": 3973, |
|
"language models effective": 3177, |
|
"language models understanding": 3239, |
|
"models llms recently": 4014, |
|
"llms recently popular": 3559, |
|
"easily implemented lines": 1700, |
|
"implemented lines code": 2768, |
|
"incontext learning fewshot": 2828, |
|
"deep neural networks": 1408, |
|
"cases ai models": 778, |
|
"study aims provide": 5980, |
|
"generative artificial intelligence": 2443, |
|
"field artificial intelligence": 2183, |
|
"powerful large language": 4771, |
|
"radford et al 2018": 5111, |
|
"generative pretrained transformer gpt": 2454, |
|
"gpt radford et al": 2500, |
|
"models large language models": 3985, |
|
"large language models produce": 3316, |
|
"language generation understanding tasks": 3146, |
|
"natural language understanding nlu": 4193, |
|
"natural language generation nlg": 4179, |
|
"natural language processing tasks": 4188, |
|
"dialog state tracking natural": 1543, |
|
"state tracking natural language": 5902, |
|
"tracking natural language generation": 6371, |
|
"current large language models": 1273, |
|
"use pretrained language models": 6619, |
|
"natural language generation models": 4178, |
|
"field natural language processing": 2186, |
|
"recently large language models": 5235, |
|
"large language models lms": 3310, |
|
"generation pretrained language models": 2423, |
|
"natural language processing nlp": 4185, |
|
"language processing nlp domain": 3251, |
|
"transformerbased large language models": 6454, |
|
"large language models llms": 3294, |
|
"large language model llm": 3283, |
|
"reasoning large language models": 5195, |
|
"large language models improved": 3289, |
|
"large language models large": 3290, |
|
"language models large language": 3192, |
|
"large language models llm": 3293, |
|
"large language models recent": 3317, |
|
"language models large lms": 3194, |
|
"generating functionally correct code": 2403, |
|
"reinforcement learning human feedback": 5303, |
|
"natural language generation tasks": 4180, |
|
"powered large language models": 4765, |
|
"ai large language models": 257, |
|
"using large language models": 6655, |
|
"search engines recommendation systems": 5591, |
|
"language models llms demonstrated": 3201, |
|
"models llms demonstrated impressive": 4005, |
|
"finetuning large language models": 2227, |
|
"language models llms using": 3218, |
|
"instructiontuning large language models": 2953, |
|
"training large language models": 6412, |
|
"analysis large language models": 329, |
|
"use large language models": 6613, |
|
"applies large language model": 385, |
|
"knowledge large language models": 3091, |
|
"models llms demonstrated remarkable": 4007, |
|
"language models llms shown": 3214, |
|
"models llms shown impressive": 4019, |
|
"llms shown impressive performance": 3567, |
|
"distillation large language models": 1619, |
|
"prediction large language models": 4797, |
|
"descriptions large language models": 1484, |
|
"recent large language models": 5218, |
|
"language models llms gpt4": 3207, |
|
"language processing nlp tasks": 3252, |
|
"language models bert gpt2": 3174, |
|
"general language understanding evaluation": 2354, |
|
"language understanding evaluation glue": 3259, |
|
"study provides valuable insights": 5992, |
|
"language models llms use": 3217, |
|
"development large language models": 1530, |
|
"natural language understanding generation": 4192, |
|
"paper aims address gap": 4499, |
|
"large language models gpt3": 3288, |
|
"ability large language models": 91, |
|
"language models llms generate": 3206, |
|
"family large language models": 2152, |
|
"research large language models": 5397, |
|
"guided generation large language": 2577, |
|
"generation large language models": 2412, |
|
"language models llms successfully": 3216, |
|
"language models llms like": 3208, |
|
"models llms like chatgpt": 4013, |
|
"named entity recognition ner": 4170, |
|
"range natural language processing": 5127, |
|
"task natural language processing": 6152, |
|
"large language models recently": 3318, |
|
"large language model text": 3284, |
|
"wide range tasks including": 6803, |
|
"language models llms exhibit": 3205, |
|
"existing evaluation benchmarks primarily": 2009, |
|
"evaluation benchmarks primarily focus": 1932, |
|
"evaluation large language models": 1940, |
|
"capabilities large language models": 734, |
|
"artificial general intelligence agi": 445, |
|
"large language models models": 3312, |
|
"breakthroughs large language models": 685, |
|
"large language models chatgpt": 3287, |
|
"llms knowledge graphs kgs": 3544, |
|
"pretrained large language models": 4849, |
|
"capabilities various nlp tasks": 741, |
|
"large language models open": 3313, |
|
"language models open ais": 3224, |
|
"multimodal large language models": 4145, |
|
"large language models mllms": 3311, |
|
"knowledge graphs kgs play": 3088, |
|
"language models varying sizes": 3242, |
|
"models varying sizes capabilities": 4096, |
|
"numerical weather prediction nwp": 4326, |
|
"models pretrained large datasets": 4051, |
|
"data large language models": 1314, |
|
"language models llms demonstrate": 3200, |
|
"language models llms revolutionized": 3213, |
|
"revolutionized natural language processing": 5484, |
|
"aligning models human values": 302, |
|
"language models llms recently": 3210, |
|
"models llms recently popular": 4015, |
|
"easily implemented lines code": 1701, |
|
"generative artificial intelligence ai": 2444, |
|
"powerful large language models": 4772, |
|
"gpt radford et al 2018": 2501, |
|
"dialog state tracking natural language": 1544, |
|
"state tracking natural language generation": 5903, |
|
"natural language processing nlp domain": 4186, |
|
"transformerbased large language models llms": 6455, |
|
"large language models large language": 3291, |
|
"language models large language models": 3193, |
|
"large language models large lms": 3292, |
|
"using large language models llms": 6656, |
|
"large language models llms demonstrated": 3297, |
|
"language models llms demonstrated impressive": 3202, |
|
"large language models llms using": 3309, |
|
"use large language models llms": 6614, |
|
"knowledge large language models llms": 3092, |
|
"language models llms demonstrated remarkable": 3203, |
|
"large language models llms shown": 3306, |
|
"language models llms shown impressive": 3215, |
|
"models llms shown impressive performance": 4020, |
|
"prediction large language models llms": 4798, |
|
"descriptions large language models llms": 1485, |
|
"models large language models llms": 3986, |
|
"large language models llms gpt4": 3301, |
|
"natural language processing nlp tasks": 4187, |
|
"general language understanding evaluation glue": 2355, |
|
"large language models llms use": 3308, |
|
"large language models llms generate": 3300, |
|
"research large language models llms": 5398, |
|
"guided generation large language models": 2578, |
|
"generation large language models large": 2413, |
|
"large language models llms successfully": 3307, |
|
"large language models llms like": 3302, |
|
"language models llms like chatgpt": 3209, |
|
"large language models llms exhibit": 3299, |
|
"existing evaluation benchmarks primarily focus": 2010, |
|
"pretrained large language models llms": 4850, |
|
"large language models open ais": 3314, |
|
"multimodal large language models mllms": 4146, |
|
"language models varying sizes capabilities": 3243, |
|
"large language models llms demonstrate": 3296, |
|
"evaluation large language models llms": 1941, |
|
"large language models llms revolutionized": 3305, |
|
"powered large language models llms": 4766, |
|
"large language models llms recently": 3303, |
|
"language models llms recently popular": 3211, |
|
"capabilities large language models llms": 735, |
|
"powerful large language models llms": 4773, |
|
"mt": 4127, |
|
"changed": 816, |
|
"paradigms": 4533, |
|
"simulation": 5766, |
|
"assigns": 467, |
|
"multihead": 4132, |
|
"heads": 2603, |
|
"adopts": 220, |
|
"crafted": 1235, |
|
"raises": 5118, |
|
"generic": 2461, |
|
"lowrank": 3612, |
|
"quantized": 5087, |
|
"phase": 4672, |
|
"reduces": 5273, |
|
"transfers": 6434, |
|
"drawn": 1681, |
|
"translations": 6469, |
|
"pretrain": 4834, |
|
"adept": 213, |
|
"spans": 5839, |
|
"paragraphs": 4534, |
|
"needing": 4216, |
|
"adhoc": 216, |
|
"topk": 6363, |
|
"nucleus": 4311, |
|
"mismatch": 3787, |
|
"generator": 2459, |
|
"closer": 882, |
|
"story": 5940, |
|
"engaging": 1824, |
|
"filter": 2193, |
|
"balance": 546, |
|
"proved": 5022, |
|
"degree": 1420, |
|
"incorporate": 2829, |
|
"tokenizer": 6345, |
|
"hidden": 2618, |
|
"elmo": 1747, |
|
"rmse": 5504, |
|
"briefly": 692, |
|
"poor": 4726, |
|
"fit": 2235, |
|
"fairly": 2139, |
|
"entire": 1859, |
|
"dietary": 1551, |
|
"sequences": 5654, |
|
"encodings": 1806, |
|
"rise": 5498, |
|
"desirable": 1498, |
|
"doing": 1647, |
|
"bidirectional": 634, |
|
"meet": 3717, |
|
"concerning": 1065, |
|
"version": 6747, |
|
"crawled": 1237, |
|
"socalled": 5801, |
|
"configurations": 1089, |
|
"ready": 5164, |
|
"scientists": 5575, |
|
"fast": 2155, |
|
"federated": 2166, |
|
"compliance": 1018, |
|
"clients": 875, |
|
"prohibitive": 4941, |
|
"chance": 814, |
|
"eliminates": 1743, |
|
"lacks": 3130, |
|
"comprises": 1040, |
|
"ladder": 3131, |
|
"recurrence": 5265, |
|
"yielding": 6863, |
|
"hashing": 2600, |
|
"mixtureofexpert": 3797, |
|
"balanced": 547, |
|
"trainable": 6383, |
|
"decomposition": 1396, |
|
"10000": 7, |
|
"throughput": 6325, |
|
"sheds": 5685, |
|
"implementations": 2765, |
|
"kind": 3075, |
|
"fuses": 2325, |
|
"place": 4693, |
|
"superglue": 6062, |
|
"discriminative": 1597, |
|
"precisely": 4785, |
|
"paid": 4486, |
|
"tutoring": 6502, |
|
"taking": 6137, |
|
"discriminator": 1598, |
|
"convergence": 1177, |
|
"pipelines": 4690, |
|
"scheduling": 5566, |
|
"consumption": 1131, |
|
"spanish": 5837, |
|
"gpt2large": 2512, |
|
"largest": 3346, |
|
"archive": 427, |
|
"extractive": 2106, |
|
"synthesized": 6103, |
|
"gpts": 2531, |
|
"unprecedented": 6581, |
|
"history": 2650, |
|
"outstanding": 4468, |
|
"composed": 1025, |
|
"barely": 550, |
|
"start": 5893, |
|
"immense": 2752, |
|
"labeler": 3113, |
|
"mcts": 3697, |
|
"satisfy": 5538, |
|
"conveying": 1190, |
|
"emotions": 1769, |
|
"formalize": 2263, |
|
"tree": 6476, |
|
"dynamically": 1689, |
|
"monte": 4115, |
|
"carlo": 768, |
|
"simpler": 5759, |
|
"really": 5173, |
|
"say": 5542, |
|
"hundreds": 2711, |
|
"enormous": 1850, |
|
"gpus": 2533, |
|
"manage": 3656, |
|
"carbon": 760, |
|
"12": 10, |
|
"draw": 1676, |
|
"repeated": 5346, |
|
"period": 4654, |
|
"entry": 1868, |
|
"unfortunately": 6556, |
|
"ranked": 5132, |
|
"missing": 3788, |
|
"ngrams": 4266, |
|
"hypotheses": 2716, |
|
"significance": 5719, |
|
"teachers": 6234, |
|
"ecommerce": 1704, |
|
"decoderonly": 1392, |
|
"background": 545, |
|
"implicitly": 2772, |
|
"captures": 758, |
|
"credible": 1247, |
|
"teach": 6230, |
|
"68": 71, |
|
"attempts": 482, |
|
"curate": 1264, |
|
"extracts": 2108, |
|
"playing": 4704, |
|
"objects": 4336, |
|
"driven": 1683, |
|
"expanding": 2021, |
|
"refers": 5284, |
|
"ordering": 4428, |
|
"induced": 2864, |
|
"heterogeneous": 2616, |
|
"variable": 6699, |
|
"joint": 3054, |
|
"heavy": 2607, |
|
"routes": 5520, |
|
"energy": 1819, |
|
"architectural": 423, |
|
"verified": 6741, |
|
"sota": 5827, |
|
"demo": 1426, |
|
"interested": 2978, |
|
"reformulate": 5291, |
|
"validates": 6691, |
|
"superiority": 6065, |
|
"openly": 4385, |
|
"permissive": 4656, |
|
"submission": 6003, |
|
"sized": 5780, |
|
"surface": 6078, |
|
"split": 5874, |
|
"wordlevel": 6821, |
|
"initializing": 2905, |
|
"calibration": 722, |
|
"gptlike": 2528, |
|
"recognized": 5249, |
|
"boundary": 672, |
|
"focuses": 2245, |
|
"compressed": 1039, |
|
"intrinsic": 2999, |
|
"15": 16, |
|
"half": 2582, |
|
"fifth": 2189, |
|
"alexa": 291, |
|
"japanese": 3050, |
|
"heldout": 2608, |
|
"fusion": 2326, |
|
"seven": 5677, |
|
"todays": 6343, |
|
"align": 298, |
|
"distill": 1614, |
|
"comes": 947, |
|
"revisit": 5479, |
|
"poorly": 4727, |
|
"runtime": 5527, |
|
"metalearning": 3731, |
|
"fine": 2207, |
|
"internal": 2985, |
|
"degradation": 1419, |
|
"execute": 1987, |
|
"leveraged": 3430, |
|
"memorizing": 3721, |
|
"memorization": 3719, |
|
"contributes": 1160, |
|
"memorize": 3720, |
|
"phases": 4673, |
|
"3d": 53, |
|
"humidity": 2710, |
|
"surpass": 6081, |
|
"17": 20, |
|
"adapter": 180, |
|
"entails": 1856, |
|
"identical": 2724, |
|
"grant": 2544, |
|
"highresource": 2644, |
|
"unannotated": 6520, |
|
"separately": 5649, |
|
"connections": 1096, |
|
"pair": 4487, |
|
"interpretation": 2992, |
|
"90": 81, |
|
"modeled": 3900, |
|
"demands": 1425, |
|
"accelerated": 113, |
|
"beams": 584, |
|
"localized": 3583, |
|
"losses": 3603, |
|
"concludes": 1069, |
|
"establishes": 1887, |
|
"exceeds": 1979, |
|
"translator": 6470, |
|
"translate": 6462, |
|
"distant": 1613, |
|
"asks": 452, |
|
"abstracts": 109, |
|
"launch": 3355, |
|
"draft": 1672, |
|
"compromising": 1042, |
|
"neglecting": 4220, |
|
"compose": 1024, |
|
"longstanding": 3599, |
|
"illustrative": 2736, |
|
"bilingual": 640, |
|
"matter": 3692, |
|
"dont": 1661, |
|
"humanlevel": 2702, |
|
"inevitable": 2872, |
|
"normalization": 4288, |
|
"drop": 1685, |
|
"contributed": 1159, |
|
"induce": 2863, |
|
"rigorously": 5497, |
|
"garnered": 2346, |
|
"fundamentally": 2320, |
|
"decreased": 1397, |
|
"aiming": 276, |
|
"subsequently": 6010, |
|
"dataflow": 1350, |
|
"exercise": 1995, |
|
"intensity": 2968, |
|
"pipelined": 4689, |
|
"shot": 5694, |
|
"accuracies": 129, |
|
"entries": 1866, |
|
"merely": 3729, |
|
"strongly": 5962, |
|
"outofdomain": 4443, |
|
"hero": 2615, |
|
"harnessing": 2599, |
|
"creation": 1243, |
|
"transforming": 6459, |
|
"wave": 6779, |
|
"dynamics": 1690, |
|
"raised": 5116, |
|
"inner": 2908, |
|
"contextaware": 1146, |
|
"higherlevel": 2626, |
|
"builds": 708, |
|
"emerged": 1758, |
|
"preventing": 4868, |
|
"defects": 1412, |
|
"transitions": 6461, |
|
"physics": 4680, |
|
"optimizer": 4417, |
|
"ease": 1695, |
|
"run": 5524, |
|
"speak": 5845, |
|
"multidimensional": 4130, |
|
"pronoun": 4977, |
|
"undertaken": 6552, |
|
"revolution": 5480, |
|
"gender": 2347, |
|
"verifying": 6744, |
|
"arbitrarily": 420, |
|
"languagebased": 3264, |
|
"simulate": 5764, |
|
"drive": 1682, |
|
"memories": 3718, |
|
"producing": 4922, |
|
"aigenerated": 271, |
|
"fiction": 2179, |
|
"designs": 1497, |
|
"contextualized": 1150, |
|
"richer": 5493, |
|
"empower": 1785, |
|
"setups": 5676, |
|
"whisper": 6799, |
|
"59": 67, |
|
"unintended": 6562, |
|
"intervention": 2995, |
|
"hallucinated": 2584, |
|
"distills": 1622, |
|
"confirmed": 1091, |
|
"humanauthored": 2692, |
|
"gigaword": 2465, |
|
"expressions": 2080, |
|
"holistic": 2654, |
|
"subquestions": 6008, |
|
"067": 1, |
|
"gaining": 2336, |
|
"schemes": 5569, |
|
"devise": 1537, |
|
"reciprocal": 5244, |
|
"rule": 5522, |
|
"inherently": 2902, |
|
"updating": 6596, |
|
"carry": 772, |
|
"bigram": 639, |
|
"difficulties": 1574, |
|
"calculated": 718, |
|
"curriculum": 1279, |
|
"slot": 5787, |
|
"41": 57, |
|
"80": 80, |
|
"stylized": 5998, |
|
"predictor": 4804, |
|
"distance": 1612, |
|
"reach": 5152, |
|
"estimator": 1891, |
|
"publication": 5045, |
|
"numeric": 4322, |
|
"partial": 4559, |
|
"pushed": 5059, |
|
"causing": 789, |
|
"market": 3672, |
|
"occupations": 4350, |
|
"weaker": 6786, |
|
"integrating": 2960, |
|
"simulator": 5769, |
|
"guiding": 2580, |
|
"regular": 5298, |
|
"index": 2853, |
|
"enforce": 1820, |
|
"matters": 3693, |
|
"portions": 4732, |
|
"calls": 725, |
|
"path": 4579, |
|
"usecases": 6620, |
|
"enterprises": 1858, |
|
"opportunity": 4406, |
|
"adequate": 214, |
|
"protection": 5018, |
|
"interdisciplinary": 2977, |
|
"examining": 1971, |
|
"bugs": 703, |
|
"immediately": 2751, |
|
"repurposed": 5371, |
|
"underlie": 6529, |
|
"solves": 5822, |
|
"specified": 5865, |
|
"005": 0, |
|
"follows": 2250, |
|
"advancing": 228, |
|
"stimulate": 5932, |
|
"trial": 6484, |
|
"multidomain": 4131, |
|
"machinelearning": 3630, |
|
"promises": 4950, |
|
"freeform": 2299, |
|
"intriguing": 2998, |
|
"closedsource": 880, |
|
"gsm8k": 2569, |
|
"game": 2338, |
|
"drawbacks": 1677, |
|
"t53b": 6123, |
|
"fault": 2157, |
|
"manufacturing": 3667, |
|
"stands": 5891, |
|
"faults": 2158, |
|
"dimension": 1580, |
|
"attentions": 487, |
|
"collective": 936, |
|
"freedom": 2298, |
|
"equips": 1874, |
|
"twofold": 6504, |
|
"auxiliary": 527, |
|
"data multiple": 1318, |
|
"sequence model": 5653, |
|
"openai gpt2": 4375, |
|
"gpt model": 2496, |
|
"components proposed": 1023, |
|
"propose implement": 4990, |
|
"performance wide": 4642, |
|
"variety natural": 6710, |
|
"models need": 4033, |
|
"embeddings large": 1753, |
|
"bert model": 615, |
|
"shown great": 5702, |
|
"models gpt2": 3967, |
|
"complex task": 1012, |
|
"finetuning models": 2229, |
|
"methods usually": 3762, |
|
"model pretraining": 3871, |
|
"like web": 3458, |
|
"qa task": 5067, |
|
"teacher models": 6233, |
|
"method significantly": 3744, |
|
"significantly outperform": 5739, |
|
"models substantial": 4076, |
|
"model inference": 3849, |
|
"multilingual language": 4136, |
|
"multiple machine": 4154, |
|
"data conduct": 1301, |
|
"model largescale": 3853, |
|
"results model": 5444, |
|
"model surpasses": 3887, |
|
"gpt2 shown": 2509, |
|
"classification sentiment": 861, |
|
"perform task": 4600, |
|
"capable generating": 750, |
|
"powerful language": 4768, |
|
"nucleus sampling": 4312, |
|
"recently introduced": 5232, |
|
"text generator": 6291, |
|
"evaluate model": 1911, |
|
"model propose": 3873, |
|
"provides good": 5031, |
|
"recent work": 5222, |
|
"models measure": 4027, |
|
"gpt language": 2494, |
|
"data domains": 1302, |
|
"evaluate proposed": 1914, |
|
"comparable performance": 968, |
|
"datasets based": 1367, |
|
"pretrained transformers": 4858, |
|
"prediction task": 4801, |
|
"extracting semantic": 2104, |
|
"features extracted": 2165, |
|
"gpt gpt2": 2493, |
|
"task train": 6159, |
|
"scenarios require": 5564, |
|
"work introduce": 6831, |
|
"introduce task": 3006, |
|
"train large": 6380, |
|
"model outperforms": 3861, |
|
"learning representations": 3407, |
|
"representations used": 5366, |
|
"learning model": 3399, |
|
"pretrained model": 4854, |
|
"network based": 4225, |
|
"train model": 6381, |
|
"models complex": 3934, |
|
"models generated": 3962, |
|
"challenging problem": 812, |
|
"control models": 1168, |
|
"story generation": 5941, |
|
"generalization capability": 2360, |
|
"corpus targeted": 1198, |
|
"training largescale": 6414, |
|
"different parameters": 1562, |
|
"additional training": 193, |
|
"generate large": 2377, |
|
"model small": 3886, |
|
"resulting model": 5429, |
|
"effectiveness method": 1727, |
|
"use fully": 6608, |
|
"data tool": 1341, |
|
"business users": 716, |
|
"data scientists": 1333, |
|
"approach leverages": 399, |
|
"like openais": 3456, |
|
"experience users": 2029, |
|
"learning finetuning": 3388, |
|
"promising approach": 4952, |
|
"models lack": 3981, |
|
"lack comprehensive": 3126, |
|
"number text": 4319, |
|
"leveraging largescale": 3438, |
|
"models text": 4084, |
|
"fewshot learners": 2174, |
|
"text prompts": 6295, |
|
"eliminates need": 1744, |
|
"provide insights": 5026, |
|
"shown provide": 5709, |
|
"dialogue tasks": 1548, |
|
"objective function": 4333, |
|
"study performance": 5989, |
|
"particular tasks": 4567, |
|
"models 175b": 3906, |
|
"adaptation lora": 178, |
|
"trainable parameters": 6384, |
|
"model quality": 3876, |
|
"model adaptation": 3815, |
|
"sheds light": 5686, |
|
"models provide": 4054, |
|
"models achieved": 3911, |
|
"tasks recent": 6208, |
|
"capabilities despite": 729, |
|
"linguistic knowledge": 3479, |
|
"knowledge world": 3103, |
|
"performance solving": 4633, |
|
"solve problems": 5817, |
|
"model easily": 3831, |
|
"knowledge graph": 3085, |
|
"surpassing human": 6084, |
|
"human performance": 2682, |
|
"attention paid": 486, |
|
"performance test": 4637, |
|
"outperforms previous": 4459, |
|
"community currently": 962, |
|
"performance models": 4623, |
|
"tasks involving": 6188, |
|
"pipeline multilingual": 4688, |
|
"english language": 1839, |
|
"transformers gpts": 6458, |
|
"trained language": 6388, |
|
"modeling objective": 3903, |
|
"outstanding performance": 4469, |
|
"generative tasks": 2458, |
|
"extractive questionanswering": 2107, |
|
"terms model": 6263, |
|
"tasks paper": 6201, |
|
"data labeler": 1309, |
|
"leads better": 3367, |
|
"data labeling": 1310, |
|
"satisfy certain": 5539, |
|
"search generation": 5592, |
|
"monte carlo": 4116, |
|
"carlo tree": 769, |
|
"tree search": 6477, |
|
"search mcts": 5593, |
|
"languages demonstrate": 3268, |
|
"hardware design": 2597, |
|
"design large": 1489, |
|
"magnitude larger": 3634, |
|
"carbon footprint": 761, |
|
"success field": 6019, |
|
"using bert": 6644, |
|
"access large": 117, |
|
"largest model": 3347, |
|
"task research": 6157, |
|
"pretraining data": 4861, |
|
"tasks limited": 6197, |
|
"hidden states": 2619, |
|
"gpt2 language": 2505, |
|
"datasets terms": 1372, |
|
"evaluating model": 1926, |
|
"semisupervised learning": 5637, |
|
"curate data": 1265, |
|
"order produce": 4426, |
|
"applications natural": 376, |
|
"effort required": 1739, |
|
"possible use": 4745, |
|
"use models": 6616, |
|
"potential large": 4755, |
|
"models capture": 3929, |
|
"potential use": 4759, |
|
"multiple metrics": 4155, |
|
"new methods": 4253, |
|
"practical use": 4780, |
|
"datasets metrics": 1370, |
|
"address propose": 208, |
|
"models building": 3926, |
|
"great performance": 2551, |
|
"proposes effective": 5013, |
|
"code demo": 893, |
|
"demo available": 1427, |
|
"model paper": 3865, |
|
"prediction tasks": 4802, |
|
"accomplish tasks": 124, |
|
"based bert": 558, |
|
"model handle": 3846, |
|
"model introduce": 3851, |
|
"openly available": 4386, |
|
"similarly sized": 5753, |
|
"models opensource": 4039, |
|
"evaluation code": 1933, |
|
"surface form": 6079, |
|
"tasks experiments": 6175, |
|
"texttotext models": 6309, |
|
"consists diverse": 1117, |
|
"summarization question": 6052, |
|
"particular summarization": 4566, |
|
"lack benchmark": 3124, |
|
"larger model": 3337, |
|
"learn robust": 3374, |
|
"greedy decoding": 2556, |
|
"extensive analysis": 2089, |
|
"improving robustness": 2808, |
|
"problem propose": 4895, |
|
"roberta gpt2": 5507, |
|
"training small": 6423, |
|
"small number": 5794, |
|
"web sources": 6795, |
|
"experiment different": 2033, |
|
"sampling methods": 5537, |
|
"data resulting": 1329, |
|
"decoderonly models": 1393, |
|
"stateoftheart sota": 5918, |
|
"present compelling": 4821, |
|
"compelling case": 991, |
|
"llm training": 3506, |
|
"models multiple": 4031, |
|
"tasks large": 6191, |
|
"impressive zeroshot": 2789, |
|
"smaller language": 5796, |
|
"demonstrated promising": 1452, |
|
"model demonstrate": 3829, |
|
"training paradigm": 6418, |
|
"downstream applications": 1664, |
|
"report performance": 5355, |
|
"taskspecific data": 6226, |
|
"baseline large": 571, |
|
"methods results": 3758, |
|
"results provide": 5447, |
|
"cost human": 1215, |
|
"systems require": 6118, |
|
"crosslingual zeroshot": 1256, |
|
"generalize new": 2363, |
|
"landscape natural": 3134, |
|
"multiple datasets": 4150, |
|
"training models": 6416, |
|
"main idea": 3639, |
|
"internal datasets": 2986, |
|
"models require": 4066, |
|
"performance existing": 4614, |
|
"success large": 6023, |
|
"memory mechanism": 3724, |
|
"ranking model": 5136, |
|
"model learn": 3854, |
|
"million parameters": 3774, |
|
"scenarios including": 5563, |
|
"systems understanding": 6120, |
|
"make following": 3650, |
|
"like gpt": 3453, |
|
"similarly better": 5752, |
|
"model pretrained": 3870, |
|
"language data": 3139, |
|
"deploying large": 1472, |
|
"performance empirically": 4612, |
|
"training multiple": 6417, |
|
"multiple downstream": 4152, |
|
"existing baselines": 2005, |
|
"benchmark test": 599, |
|
"strategy named": 5945, |
|
"spoken language": 5876, |
|
"performance chatgpt": 4604, |
|
"sampling algorithm": 5536, |
|
"single token": 5774, |
|
"starting point": 5896, |
|
"results case": 5432, |
|
"data natural": 1319, |
|
"llms require": 3561, |
|
"benefits using": 611, |
|
"accuracy downstream": 131, |
|
"textual representations": 6312, |
|
"improve training": 2793, |
|
"increase accuracy": 2837, |
|
"demonstrate use": 1448, |
|
"chatgpt gpt4": 831, |
|
"considerable attention": 1103, |
|
"issues propose": 3041, |
|
"glue datasets": 2481, |
|
"variety downstream": 6707, |
|
"expertise machine": 2051, |
|
"promising technique": 4955, |
|
"counterparts furthermore": 1225, |
|
"compute resources": 1053, |
|
"endtoend training": 1818, |
|
"execution model": 1992, |
|
"years large": 6858, |
|
"zero shot": 6867, |
|
"paper evaluate": 4506, |
|
"evaluate ability": 1903, |
|
"perform arithmetic": 4596, |
|
"knowledge training": 3101, |
|
"tasks propose": 6203, |
|
"way improve": 6782, |
|
"model performs": 3869, |
|
"multiple text": 4157, |
|
"achieved average": 148, |
|
"average f1": 537, |
|
"f1 scores": 2113, |
|
"using models": 6661, |
|
"models developed": 3940, |
|
"generation generative": 2409, |
|
"success various": 6027, |
|
"challenges need": 808, |
|
"need addressed": 4209, |
|
"applications sentence": 379, |
|
"achieve significant": 142, |
|
"powerful tools": 4775, |
|
"tools natural": 6354, |
|
"millions parameters": 3776, |
|
"used train": 6624, |
|
"produce fluent": 4918, |
|
"new paradigm": 4254, |
|
"models evaluation": 3948, |
|
"performance improvements": 4620, |
|
"realworld use": 5182, |
|
"outperforms strong": 4461, |
|
"built large": 710, |
|
"models ai": 3915, |
|
"cognitive science": 920, |
|
"llms code": 3520, |
|
"online demo": 4366, |
|
"propose using": 5003, |
|
"model chatgpt": 3824, |
|
"findings demonstrate": 2204, |
|
"work formalize": 6829, |
|
"formalize task": 2264, |
|
"study contributes": 5981, |
|
"speech processing": 5868, |
|
"content classification": 1137, |
|
"exceeds performance": 1980, |
|
"performance discuss": 4610, |
|
"instructiontuned large": 2948, |
|
"longform text": 3597, |
|
"expressed natural": 2078, |
|
"language instructions": 3148, |
|
"hallucinations produced": 2588, |
|
"novel benchmark": 4299, |
|
"addition propose": 190, |
|
"develop new": 1520, |
|
"human intervention": 2678, |
|
"hallucinated content": 2585, |
|
"ability generate": 88, |
|
"model generated": 3841, |
|
"175b parameter": 25, |
|
"evaluations furthermore": 1954, |
|
"unseen domains": 6586, |
|
"systems using": 6121, |
|
"method leverages": 3742, |
|
"data similar": 1335, |
|
"model sizes": 3885, |
|
"observe large": 4340, |
|
"scoring model": 5582, |
|
"training training": 6428, |
|
"schemes based": 5570, |
|
"able exploit": 100, |
|
"comprehensive experiments": 1037, |
|
"demonstrate time": 1447, |
|
"analysis training": 335, |
|
"training process": 6420, |
|
"training study": 6424, |
|
"performance language": 4621, |
|
"including language": 2819, |
|
"model proposed": 3874, |
|
"training time": 6426, |
|
"entire training": 1860, |
|
"using language": 6651, |
|
"plays crucial": 4706, |
|
"crucial role": 1259, |
|
"metric based": 3765, |
|
"based large": 563, |
|
"chainofthought cot": 798, |
|
"cot prompting": 1220, |
|
"method combines": 3738, |
|
"approaches furthermore": 410, |
|
"earlier models": 1692, |
|
"models advanced": 3914, |
|
"models tend": 4083, |
|
"making difficult": 3655, |
|
"using methods": 6659, |
|
"problem work": 4896, |
|
"propose endtoend": 4988, |
|
"llm using": 3507, |
|
"demonstrate potential": 1444, |
|
"enables flexible": 1794, |
|
"evaluation llms": 1942, |
|
"llms vision": 3578, |
|
"leverages existing": 3432, |
|
"generation process": 2425, |
|
"process significantly": 4904, |
|
"mechanism llms": 3710, |
|
"long input": 3593, |
|
"input sentences": 2917, |
|
"demonstrate approach": 1431, |
|
"model scales": 3879, |
|
"translation tasks": 6468, |
|
"compute data": 1052, |
|
"significantly improve": 5735, |
|
"practice training": 4782, |
|
"llms specific": 3568, |
|
"learning settings": 3409, |
|
"build endtoend": 705, |
|
"programming interfaces": 4933, |
|
"llms limited": 3547, |
|
"behavioral testing": 587, |
|
"range capabilities": 5123, |
|
"llms approach": 3514, |
|
"human effort": 2667, |
|
"important differences": 2779, |
|
"learning reason": 3406, |
|
"forward pass": 2276, |
|
"optimization problems": 4414, |
|
"improved performance": 2795, |
|
"predict future": 4791, |
|
"tasks highly": 6181, |
|
"similar large": 5746, |
|
"comprehensive benchmark": 1034, |
|
"assess performance": 457, |
|
"models traditional": 4085, |
|
"chinese benchmarks": 846, |
|
"model model": 3857, |
|
"multiple domains": 4151, |
|
"jointly train": 3056, |
|
"framework called": 2288, |
|
"trained jointly": 6387, |
|
"limited availability": 3466, |
|
"llms emerged": 3532, |
|
"performance gpt4": 4618, |
|
"gpt4 llm": 2524, |
|
"feature engineering": 2163, |
|
"powerful llms": 4774, |
|
"limited capability": 3467, |
|
"models similar": 4072, |
|
"public benchmarks": 5042, |
|
"medicine law": 3716, |
|
"style transfer": 5995, |
|
"applicable scenarios": 371, |
|
"largescale data": 3340, |
|
"impact large": 2755, |
|
"shown promise": 5706, |
|
"quality based": 5075, |
|
"alignment human": 304, |
|
"compare approach": 973, |
|
"performance previous": 4628, |
|
"error rate": 1880, |
|
"models given": 3965, |
|
"existing works": 2017, |
|
"input data": 2915, |
|
"sota baseline": 5828, |
|
"strong ability": 5954, |
|
"model families": 3836, |
|
"variety natural language": 6711, |
|
"embeddings large language": 1754, |
|
"tasks like web": 6196, |
|
"multilingual language models": 4137, |
|
"experimental results model": 2039, |
|
"nlp tasks text": 4274, |
|
"tasks text classification": 6216, |
|
"text classification sentiment": 6278, |
|
"classification sentiment analysis": 862, |
|
"powerful language models": 4769, |
|
"propose novel approach": 4997, |
|
"gpt language model": 2495, |
|
"method significantly outperforms": 3746, |
|
"significantly outperforms baselines": 5741, |
|
"based generative pretrained": 561, |
|
"model outperforms existing": 3862, |
|
"generation large pretrained": 2414, |
|
"stateoftheart language models": 5911, |
|
"largescale language models": 3344, |
|
"text corpus targeted": 6282, |
|
"language models lack": 3189, |
|
"leveraging largescale language": 3439, |
|
"language models text": 3236, |
|
"language model adaptation": 3154, |
|
"knowledge world knowledge": 3104, |
|
"results model outperforms": 5445, |
|
"model outperforms stateoftheart": 3863, |
|
"language models work": 3244, |
|
"generative pretrained transformers": 2455, |
|
"pretrained transformers gpts": 4859, |
|
"monte carlo tree": 4117, |
|
"carlo tree search": 770, |
|
"tree search mcts": 6478, |
|
"success field natural": 6020, |
|
"downstream tasks limited": 1671, |
|
"gpt2 language models": 2506, |
|
"language models achieved": 3169, |
|
"applications natural language": 377, |
|
"potential large language": 4756, |
|
"paper proposes effective": 4528, |
|
"language models using": 3240, |
|
"summarization question answering": 6053, |
|
"lack benchmark datasets": 3125, |
|
"address problem propose": 207, |
|
"bert roberta gpt2": 617, |
|
"language model using": 3164, |
|
"tasks large language": 6192, |
|
"performance wide range": 4643, |
|
"landscape natural language": 3135, |
|
"success large language": 6024, |
|
"multiple downstream tasks": 4153, |
|
"significantly outperforms existing": 5742, |
|
"outperforms existing baselines": 4457, |
|
"data natural language": 1320, |
|
"accuracy downstream tasks": 132, |
|
"results case study": 5433, |
|
"variety downstream tasks": 6708, |
|
"expertise machine learning": 2052, |
|
"recent years large": 5225, |
|
"years large language": 6859, |
|
"achieved average f1": 149, |
|
"results demonstrate effectiveness": 5436, |
|
"challenges need addressed": 809, |
|
"tools natural language": 6355, |
|
"introduce new paradigm": 3003, |
|
"language models suggest": 3235, |
|
"language models study": 3233, |
|
"built large language": 711, |
|
"online demo available": 4367, |
|
"language model chatgpt": 3155, |
|
"demonstrated impressive zeroshot": 1451, |
|
"longform text generation": 3598, |
|
"expressed natural language": 2079, |
|
"natural language instructions": 4182, |
|
"minimal human intervention": 3782, |
|
"human evaluations furthermore": 2670, |
|
"models work investigate": 4100, |
|
"tasks including language": 6184, |
|
"plays crucial role": 4707, |
|
"based large language": 564, |
|
"chainofthought cot prompting": 799, |
|
"method significantly improves": 3745, |
|
"language models advanced": 3171, |
|
"common practice training": 953, |
|
"language models traditional": 3237, |
|
"tasks propose novel": 6204, |
|
"models llms emerged": 4008, |
|
"demonstrated remarkable performance": 1455, |
|
"language models complex": 3176, |
|
"impact large language": 2756, |
|
"large language models trained": 3321, |
|
"embeddings large language models": 1755, |
|
"nlp tasks text classification": 4275, |
|
"tasks text classification sentiment": 6217, |
|
"text classification sentiment analysis": 6279, |
|
"paper propose novel approach": 4525, |
|
"method significantly outperforms baselines": 3747, |
|
"pretrained language model gpt2": 4843, |
|
"leveraging largescale language models": 3440, |
|
"generative pretrained transformers gpts": 2456, |
|
"monte carlo tree search": 4118, |
|
"carlo tree search mcts": 771, |
|
"success field natural language": 6021, |
|
"applications natural language processing": 378, |
|
"potential large language models": 4757, |
|
"largescale language model llm": 3343, |
|
"tasks large language models": 6193, |
|
"large language models achieved": 3286, |
|
"landscape natural language processing": 3136, |
|
"success large language models": 6025, |
|
"significantly outperforms existing baselines": 5743, |
|
"recent years large language": 5226, |
|
"years large language models": 6860, |
|
"tools natural language processing": 6356, |
|
"large language models study": 3319, |
|
"large language model chatgpt": 3282, |
|
"llms demonstrated impressive zeroshot": 3526, |
|
"based large language models": 565, |
|
"pretrained large language model": 4848, |
|
"language models llms emerged": 3204, |
|
"transformerbased large language model": 6452, |
|
"nlp tasks text classification sentiment": 4276, |
|
"tasks text classification sentiment analysis": 6218, |
|
"monte carlo tree search mcts": 4119, |
|
"success field natural language processing": 6022, |
|
"success large language models llm": 6026, |
|
"recent years large language models": 5227, |
|
"models llms demonstrated impressive zeroshot": 4006, |
|
"based large language models llms": 566, |
|
"training large language models llms": 6413, |
|
"large language models llms emerged": 3298, |
|
"transformerbased large language model llm": 6453, |
|
"development large language models llms": 1531, |
|
"trees": 6479, |
|
"markov": 3673, |
|
"puzzle": 5061, |
|
"verifier": 6742, |
|
"depend": 1463, |
|
"string": 5952, |
|
"tries": 6485, |
|
"acceptance": 115, |
|
"positions": 4739, |
|
"invalid": 3016, |
|
"offset": 4360, |
|
"display": 1609, |
|
"dealing": 1379, |
|
"styled": 5996, |
|
"account": 127, |
|
"keystrokes": 3068, |
|
"codewriting": 912, |
|
"docstrings": 1637, |
|
"114": 9, |
|
"safety": 5529, |
|
"economics": 1706, |
|
"fooling": 2252, |
|
"2000": 30, |
|
"plagiarism": 4694, |
|
"discussion": 1605, |
|
"consideration": 1105, |
|
"unit": 6565, |
|
"file": 2191, |
|
"ranker": 5133, |
|
"kinds": 3076, |
|
"coverage": 1230, |
|
"executes": 1989, |
|
"codedavinci002": 908, |
|
"inadequate": 2811, |
|
"repository": 5360, |
|
"socially": 5804, |
|
"politically": 4724, |
|
"parent": 4556, |
|
"multihop": 4133, |
|
"adaption": 183, |
|
"specifications": 5864, |
|
"conducting": 1084, |
|
"imagine": 2744, |
|
"gives": 2476, |
|
"bridging": 690, |
|
"turing": 6498, |
|
"connection": 1095, |
|
"inherent": 2901, |
|
"perception": 4592, |
|
"groundbreaking": 2559, |
|
"connect": 1094, |
|
"realization": 5170, |
|
"localizing": 3584, |
|
"consensus": 1098, |
|
"incorporates": 2831, |
|
"planning": 4698, |
|
"userfriendly": 6633, |
|
"tables": 6124, |
|
"generalized": 2364, |
|
"planners": 4697, |
|
"tendency": 6254, |
|
"hallucinate": 2583, |
|
"hallucination": 2586, |
|
"did": 1550, |
|
"basis": 577, |
|
"closed": 878, |
|
"exposing": 2075, |
|
"regulation": 5299, |
|
"day": 1375, |
|
"tackling": 6128, |
|
"barrier": 551, |
|
"principles": 4882, |
|
"unparalleled": 6580, |
|
"responsible": 5422, |
|
"completing": 1003, |
|
"empowered": 1786, |
|
"implementing": 2769, |
|
"intersection": 2993, |
|
"humancomputer": 2694, |
|
"interact": 2972, |
|
"reflect": 5289, |
|
"uncertainty": 6524, |
|
"knowing": 3078, |
|
"executionbased": 1994, |
|
"modelgenerated": 3901, |
|
"undefined": 6528, |
|
"presence": 4819, |
|
"inclusion": 2820, |
|
"hurdles": 2712, |
|
"tailor": 6133, |
|
"thoughts": 6322, |
|
"daily": 1289, |
|
"led": 3420, |
|
"problemsolving": 4899, |
|
"proficiency": 4928, |
|
"manifest": 3657, |
|
"knowledgebase": 3106, |
|
"publications": 5046, |
|
"79": 77, |
|
"sustainable": 6090, |
|
"calculating": 719, |
|
"googles": 2489, |
|
"bard": 549, |
|
"anthropics": 359, |
|
"vulnerable": 6777, |
|
"viable": 6751, |
|
"gpt4s": 2525, |
|
"underscoring": 6536, |
|
"logs": 3591, |
|
"biology": 651, |
|
"overlooked": 4482, |
|
"confounding": 1092, |
|
"rigor": 5496, |
|
"correlated": 1206, |
|
"unleash": 6574, |
|
"controllers": 1172, |
|
"friendly": 2306, |
|
"realizing": 5172, |
|
"bootstrapping": 667, |
|
"perceive": 4589, |
|
"discipline": 1588, |
|
"convey": 1189, |
|
"coupled": 1226, |
|
"solved": 5820, |
|
"frame": 2283, |
|
"multistep": 4159, |
|
"validity": 6693, |
|
"checks": 841, |
|
"concerned": 1064, |
|
"repeatedly": 5347, |
|
"queried": 5089, |
|
"subtle": 6017, |
|
"presenting": 4829, |
|
"code completion": 890, |
|
"trained code": 6386, |
|
"discuss challenges": 1600, |
|
"open problems": 4371, |
|
"performs best": 4653, |
|
"user study": 6632, |
|
"significant impact": 5722, |
|
"collect data": 931, |
|
"completion models": 1005, |
|
"taking account": 6138, |
|
"evaluating large": 1922, |
|
"programs docstrings": 4936, |
|
"detection techniques": 1511, |
|
"simulation models": 5767, |
|
"models systems": 4080, |
|
"systems given": 6114, |
|
"generate correct": 2374, |
|
"generated programs": 2395, |
|
"different kinds": 1558, |
|
"models natural": 4032, |
|
"leverages pretrained": 3434, |
|
"reducing human": 5275, |
|
"different pretrained": 1563, |
|
"improves pass1": 2800, |
|
"pass1 metric": 4574, |
|
"absolute improvement": 105, |
|
"codedavinci002 model": 909, |
|
"using natural": 6662, |
|
"specific language": 5857, |
|
"constrained decoding": 1121, |
|
"capabilities models": 736, |
|
"synthesis large": 6098, |
|
"requires understanding": 5380, |
|
"based pretrained": 568, |
|
"newly collected": 4262, |
|
"model significantly": 3881, |
|
"query language": 5092, |
|
"language large": 3150, |
|
"models language": 3982, |
|
"model user": 3896, |
|
"external tools": 2099, |
|
"tasks complex": 6171, |
|
"highlevel semantics": 2629, |
|
"efficacy employing": 1730, |
|
"execution accuracy": 1991, |
|
"significantly better": 5732, |
|
"recently emerged": 5231, |
|
"ability llms": 92, |
|
"llm capabilities": 3499, |
|
"currently lack": 1278, |
|
"task results": 6158, |
|
"results llms": 5442, |
|
"descriptions paper": 1486, |
|
"approach establish": 395, |
|
"promote development": 4957, |
|
"approach enables": 394, |
|
"research introduces": 5394, |
|
"llm visual": 3508, |
|
"utilizing llms": 6684, |
|
"introduces novel": 3011, |
|
"user interface": 6631, |
|
"incorporate ideas": 2830, |
|
"demonstrate benefits": 1432, |
|
"humans llms": 2706, |
|
"execution time": 1993, |
|
"times faster": 6336, |
|
"potential effective": 4754, |
|
"framework involves": 2291, |
|
"errors automatic": 1882, |
|
"models generation": 3963, |
|
"given task": 2472, |
|
"tasks generate": 6179, |
|
"domain particular": 1652, |
|
"python programs": 5063, |
|
"evaluate approach": 1904, |
|
"recently models": 5236, |
|
"api calls": 364, |
|
"successful integration": 6030, |
|
"researchers explored": 5401, |
|
"compare models": 974, |
|
"llms rely": 3560, |
|
"analyzing common": 341, |
|
"adapt model": 174, |
|
"software tools": 5810, |
|
"demonstrate techniques": 1446, |
|
"openai gpt4": 4376, |
|
"recipe practical": 5242, |
|
"recently deep": 5230, |
|
"types models": 6513, |
|
"data features": 1305, |
|
"design principles": 1490, |
|
"principles architecture": 4883, |
|
"generation llms": 2415, |
|
"llms chatgpt": 3519, |
|
"replace human": 5350, |
|
"chatgpt various": 835, |
|
"usage llms": 6603, |
|
"enhancing security": 1849, |
|
"llms responsible": 3562, |
|
"diverse scenarios": 1630, |
|
"individuals society": 2861, |
|
"llms paramount": 3552, |
|
"humancomputer interaction": 2695, |
|
"human understanding": 2688, |
|
"lessons learned": 3424, |
|
"use information": 6610, |
|
"challenges arise": 807, |
|
"perspective ai": 4664, |
|
"reasoning paper": 5197, |
|
"task completion": 6145, |
|
"framework quantify": 2294, |
|
"recent months": 5219, |
|
"potential artificial": 4753, |
|
"solving tasks": 5824, |
|
"present contribution": 4823, |
|
"challenge present": 803, |
|
"present new": 4825, |
|
"prompt generation": 4964, |
|
"performance improvement": 4619, |
|
"tasks code": 6169, |
|
"users need": 6637, |
|
"code models": 898, |
|
"release dataset": 5318, |
|
"googles bard": 2490, |
|
"anthropics claude": 360, |
|
"capability large": 744, |
|
"comparing performance": 985, |
|
"llms potential": 3553, |
|
"trained using": 6393, |
|
"data trained": 1342, |
|
"results experiments": 5437, |
|
"proposed llm": 5008, |
|
"existing models": 2014, |
|
"effective solution": 1721, |
|
"data offers": 1323, |
|
"performance multiple": 4624, |
|
"design implementation": 1488, |
|
"causal effect": 783, |
|
"engineering methods": 1829, |
|
"performance average": 4603, |
|
"tasks growing": 6180, |
|
"equips llms": 1875, |
|
"seamless integration": 5586, |
|
"intelligent assistant": 2966, |
|
"utilize large": 6677, |
|
"domains paper": 1657, |
|
"framework tailored": 2296, |
|
"present comprehensive": 4822, |
|
"supervised finetuning": 6068, |
|
"potential advantages": 4751, |
|
"performance current": 4608, |
|
"believe work": 592, |
|
"gap human": 2342, |
|
"human intent": 2676, |
|
"language utterances": 3263, |
|
"approach uses": 403, |
|
"tools like": 6353, |
|
"problem present": 4894, |
|
"evaluate effectiveness": 1906, |
|
"evaluated multiple": 1918, |
|
"models increasingly": 3977, |
|
"models general": 3959, |
|
"approach effective": 393, |
|
"overall quality": 4473, |
|
"models model": 4029, |
|
"assumes paramount": 475, |
|
"paramount importance": 4550, |
|
"llm able": 3497, |
|
"engineering efforts": 1828, |
|
"evaluating large language": 1923, |
|
"transformerbased language model": 6448, |
|
"language models natural": 3222, |
|
"leverages pretrained language": 3435, |
|
"improves pass1 metric": 2801, |
|
"using natural language": 6663, |
|
"synthesis large language": 6099, |
|
"work propose novel": 6836, |
|
"model significantly outperforms": 3882, |
|
"language large language": 3151, |
|
"complex tasks challenging": 1014, |
|
"paper introduces novel": 4513, |
|
"using language model": 6652, |
|
"language model generate": 3157, |
|
"language models generation": 3183, |
|
"code model data": 897, |
|
"models llms rely": 4016, |
|
"models work propose": 4101, |
|
"language models ai": 3172, |
|
"capability large language": 745, |
|
"prompt engineering methods": 4962, |
|
"utilize large language": 6678, |
|
"models llms chatgpt": 4002, |
|
"natural language utterances": 4194, |
|
"evaluating large language models": 1924, |
|
"synthesis large language models": 6100, |
|
"model significantly outperforms existing": 3883, |
|
"language large language models": 3152, |
|
"performance wide range tasks": 4644, |
|
"language models llms rely": 3212, |
|
"capability large language models": 746, |
|
"utilize large language models": 6679, |
|
"language models llms chatgpt": 3199, |
|
"large language models llms rely": 3304, |
|
"capability large language models llms": 747, |
|
"large language models llms chatgpt": 3295, |
|
"turns": 6501, |
|
"gpt23": 2511, |
|
"blocks": 656, |
|
"action": 164, |
|
"simulated": 5765, |
|
"bot": 668, |
|
"simulators": 5770, |
|
"ties": 6328, |
|
"nonsensical": 4284, |
|
"dialogues": 1549, |
|
"humangenerated": 2698, |
|
"accessed": 119, |
|
"frozen": 2308, |
|
"speakers": 5847, |
|
"fake": 2141, |
|
"breaks": 680, |
|
"vastly": 6735, |
|
"detector": 1512, |
|
"98": 84, |
|
"grammatical": 2540, |
|
"engagement": 1823, |
|
"reversals": 5475, |
|
"roles": 5514, |
|
"94": 82, |
|
"games": 2339, |
|
"creative": 1244, |
|
"proxies": 5036, |
|
"forum": 2274, |
|
"fall": 2142, |
|
"reaction": 5156, |
|
"cognition": 915, |
|
"moves": 4126, |
|
"technological": 6245, |
|
"leap": 3372, |
|
"labor": 3120, |
|
"lives": 3491, |
|
"28": 42, |
|
"divides": 1635, |
|
"amazon": 317, |
|
"funding": 2321, |
|
"experiencing": 2031, |
|
"contributing": 1161, |
|
"addresses": 210, |
|
"enrich": 1851, |
|
"unexpected": 6555, |
|
"freezing": 2301, |
|
"lost": 3604, |
|
"pertinent": 4668, |
|
"tuned": 6495, |
|
"deliberation": 1422, |
|
"classified": 866, |
|
"continuously": 1154, |
|
"subcategories": 5999, |
|
"unresolved": 6584, |
|
"variability": 6698, |
|
"underscore": 6534, |
|
"subsequent": 6009, |
|
"identity": 2730, |
|
"center": 791, |
|
"excited": 1985, |
|
"battery": 580, |
|
"notwithstanding": 4296, |
|
"pursuit": 5058, |
|
"multiagent": 4129, |
|
"beings": 590, |
|
"tied": 6327, |
|
"remedies": 5341, |
|
"unpredictable": 6582, |
|
"winning": 6814, |
|
"segments": 5604, |
|
"possibly": 4746, |
|
"disciplines": 1589, |
|
"imagery": 2741, |
|
"creators": 1246, |
|
"master": 3679, |
|
"increasingly capable": 2842, |
|
"based models": 567, |
|
"new framework": 4249, |
|
"domain task": 1654, |
|
"training approach": 6395, |
|
"using reinforcement": 6666, |
|
"fine tune": 2208, |
|
"learning approach": 3382, |
|
"work study": 6838, |
|
"agents large": 241, |
|
"relevant information": 5323, |
|
"model evaluate": 3833, |
|
"generate responses": 2383, |
|
"demonstrate large": 1438, |
|
"al 2019": 287, |
|
"gpt3 vastly": 2518, |
|
"models publicly": 4056, |
|
"data quality": 1326, |
|
"sequential questions": 5658, |
|
"contribution work": 1164, |
|
"context memory": 1142, |
|
"memory multistep": 3725, |
|
"humans typically": 2708, |
|
"framework combines": 2289, |
|
"ideas large": 2721, |
|
"providing feedback": 5035, |
|
"realworld engagement": 5178, |
|
"finetune language": 2211, |
|
"fall short": 2143, |
|
"ai researchers": 261, |
|
"exhibit remarkable": 1998, |
|
"variety domains": 6706, |
|
"challenges ahead": 806, |
|
"language multimodal": 3245, |
|
"multimodal models": 4148, |
|
"raised concerns": 5117, |
|
"ai human": 254, |
|
"unlike conventional": 6576, |
|
"model generates": 3842, |
|
"short period": 5690, |
|
"period time": 4655, |
|
"certain cases": 795, |
|
"preliminary study": 4811, |
|
"plays important": 4708, |
|
"important role": 2780, |
|
"daily lives": 1290, |
|
"analysis largescale": 330, |
|
"research development": 5387, |
|
"demonstrate ability": 1430, |
|
"understanding llms": 6546, |
|
"language translation": 3256, |
|
"examine impact": 1968, |
|
"text image": 6293, |
|
"ai technology": 264, |
|
"language corpora": 3138, |
|
"role enhancing": 5513, |
|
"services using": 5666, |
|
"comparative analysis": 970, |
|
"understanding conversational": 6541, |
|
"recognition asr": 5246, |
|
"add additional": 187, |
|
"7b model": 79, |
|
"generate new": 2379, |
|
"models success": 4078, |
|
"combines large": 943, |
|
"predefined set": 4788, |
|
"work explore": 6828, |
|
"implementation generative": 2763, |
|
"science using": 5572, |
|
"llms challenges": 3518, |
|
"augment human": 495, |
|
"results human": 5440, |
|
"llms reasoning": 3557, |
|
"various llm": 6719, |
|
"vision language": 6758, |
|
"emotional labels": 1768, |
|
"fell short": 2171, |
|
"evaluating models": 1927, |
|
"decisionmaking information": 1389, |
|
"human ones": 2681, |
|
"compared human": 980, |
|
"nature large": 4197, |
|
"community lacks": 963, |
|
"building general": 707, |
|
"perform comprehensive": 4599, |
|
"general framework": 2349, |
|
"perception action": 4593, |
|
"human beings": 2666, |
|
"human reasoning": 2685, |
|
"reasoning decisionmaking": 5191, |
|
"prompting chatgpt": 4968, |
|
"understanding paper": 6548, |
|
"phenomenon hand": 4676, |
|
"leads new": 3368, |
|
"using reinforcement learning": 6667, |
|
"agents large language": 242, |
|
"model generate responses": 3840, |
|
"demonstrate large language": 1439, |
|
"et al 2019": 1895, |
|
"models publicly available": 4057, |
|
"context memory multistep": 1143, |
|
"ideas large language": 2722, |
|
"short period time": 5691, |
|
"plays important role": 4709, |
|
"generative ai technology": 2441, |
|
"speech recognition asr": 5870, |
|
"language models success": 3234, |
|
"combines large language": 944, |
|
"models work explore": 4099, |
|
"implementation generative ai": 2764, |
|
"nature large language": 4198, |
|
"generative ai models": 2440, |
|
"agents large language models": 243, |
|
"demonstrate large language models": 1440, |
|
"ideas large language models": 2723, |
|
"automatic speech recognition asr": 513, |
|
"large language models success": 3320, |
|
"nature large language models": 4199, |
|
"demonstrate large language models llms": 1441, |
|
"oracle": 4422, |
|
"crafting": 1236, |
|
"prerequisite": 4818, |
|
"expense": 2025, |
|
"21": 41, |
|
"nowadays": 4308, |
|
"distinguish": 1624, |
|
"investigations": 3025, |
|
"portion": 4731, |
|
"attributable": 489, |
|
"refines": 5287, |
|
"suitability": 6043, |
|
"pioneering": 4686, |
|
"dl": 1636, |
|
"counter": 1221, |
|
"notes": 4294, |
|
"strict": 5950, |
|
"phrases": 4678, |
|
"corporate": 1196, |
|
"delves": 1423, |
|
"capitalization": 754, |
|
"college": 937, |
|
"archives": 428, |
|
"keyword": 3069, |
|
"reconstruction": 5258, |
|
"termed": 6259, |
|
"book": 661, |
|
"signatures": 5718, |
|
"models focus": 3956, |
|
"detection task": 1510, |
|
"dataset named": 1360, |
|
"create dataset": 1239, |
|
"compared baseline": 977, |
|
"data sources": 1338, |
|
"leading creation": 3365, |
|
"enabling model": 1798, |
|
"second challenge": 5596, |
|
"responses grounded": 5421, |
|
"models performs": 4047, |
|
"propose various": 5004, |
|
"finetuned machine": 2218, |
|
"base models": 556, |
|
"model outputs": 3864, |
|
"datasets experimental": 1368, |
|
"future investigations": 2329, |
|
"text second": 6296, |
|
"public available": 5041, |
|
"multimodal dataset": 4142, |
|
"generated llms": 2392, |
|
"facilitate comprehensive": 2119, |
|
"expensive timeconsuming": 2027, |
|
"opensource implementations": 4391, |
|
"technical terms": 6240, |
|
"write complex": 6851, |
|
"day paper": 1376, |
|
"approaches like": 411, |
|
"model able": 3810, |
|
"research contributes": 5386, |
|
"ai text": 265, |
|
"model generating": 3843, |
|
"datasets used": 1373, |
|
"neural model": 4233, |
|
"2023 conference": 39, |
|
"issue large": 3035, |
|
"finetuning techniques": 2233, |
|
"llms improve": 3539, |
|
"language models focus": 3181, |
|
"access large collection": 118, |
|
"models paper introduces": 4043, |
|
"generated large language": 2390, |
|
"issue large language": 3036, |
|
"large language models paper": 3315, |
|
"generated large language model": 2391, |
|
"issue large language models": 3037, |
|
"motion": 4121, |
|
"spaces": 5835, |
|
"converts": 1188, |
|
"asking": 451, |
|
"formulation": 2273, |
|
"integrates": 2959, |
|
"videos": 6753, |
|
"video": 6752, |
|
"struggled": 5971, |
|
"compositional": 1027, |
|
"harder": 2595, |
|
"audio": 492, |
|
"tackles": 6127, |
|
"prototype": 5020, |
|
"immediate": 2750, |
|
"embodiment": 1756, |
|
"strengthen": 5948, |
|
"aligns": 305, |
|
"64": 69, |
|
"dalle": 1291, |
|
"encounter": 1809, |
|
"paired": 4488, |
|
"expressive": 2081, |
|
"richness": 5494, |
|
"suffering": 6033, |
|
"pinpoint": 4685, |
|
"textguided": 6302, |
|
"maximize": 3694, |
|
"textonly": 6303, |
|
"conventional methods": 1176, |
|
"automatic generation": 507, |
|
"model information": 3850, |
|
"overcome limitation": 4477, |
|
"information facilitating": 2886, |
|
"generating novel": 2405, |
|
"similar problems": 5748, |
|
"time ai": 6330, |
|
"understanding ability": 6539, |
|
"knowledge reasoning": 3096, |
|
"text understanding": 6300, |
|
"makes possible": 3653, |
|
"audio encoder": 493, |
|
"demonstrate impressive": 1437, |
|
"method achieved": 3734, |
|
"new capabilities": 4244, |
|
"existing foundation": 2011, |
|
"various types": 6728, |
|
"allowing users": 312, |
|
"users query": 6638, |
|
"models benchmark": 3922, |
|
"research introduce": 5393, |
|
"encodes text": 1804, |
|
"manipulation tasks": 3660, |
|
"rlhf large": 5503, |
|
"feedback rlhf": 2169, |
|
"achieves stateoftheart performance": 156, |
|
"proposed method achieved": 5010, |
|
"existing foundation models": 2012, |
|
"human feedback rlhf": 2674, |
|
"learning human feedback rlhf": 3392, |
|
"reinforcement learning human feedback rlhf": 5304, |
|
"accordingly": 126, |
|
"record": 5259, |
|
"primitive": 4881, |
|
"398": 52, |
|
"bounded": 673, |
|
"opinions": 4403, |
|
"acquiring": 161, |
|
"parse": 4557, |
|
"reductions": 5277, |
|
"inhouse": 2903, |
|
"pushes": 5060, |
|
"mode": 3808, |
|
"capacities": 752, |
|
"striking": 5951, |
|
"chemistry": 843, |
|
"mines": 3779, |
|
"alleviate problem": 307, |
|
"cognitive architecture": 918, |
|
"llms trained": 3573, |
|
"llms new": 3549, |
|
"improves stateoftheart": 2803, |
|
"presents novel": 4831, |
|
"deeper insights": 1410, |
|
"method incorporates": 3740, |
|
"different prompt": 1564, |
|
"engineering techniques": 1831, |
|
"prompting schemes": 4972, |
|
"cognitive abilities": 917, |
|
"zeroshot chainofthought": 6871, |
|
"chainofthought prompting": 800, |
|
"language models language": 3190, |
|
"paper presents novel": 4520, |
|
"different prompt engineering": 1565, |
|
"prompt engineering techniques": 4963, |
|
"zeroshot chainofthought prompting": 6872, |
|
"different prompt engineering techniques": 1566, |
|
"converting": 1187, |
|
"nbest": 4200, |
|
"palm2": 4491, |
|
"conceptually": 1061, |
|
"humans machines": 2707, |
|
"evaluated using": 1919, |
|
"optimization framework": 4412, |
|
"separately trained": 5650, |
|
"results using": 5451, |
|
"experiments multiple": 2047, |
|
"achieved remarkable": 150, |
|
"processing enabling": 4908, |
|
"semantic space": 5626, |
|
"face challenges": 2116, |
|
"prompt based": 4959, |
|
"demonstrate compared": 1433, |
|
"llms promising": 3555, |
|
"conceptually simple": 1062, |
|
"llms effective": 3530, |
|
"effective alternative": 1717, |
|
"dataset compared": 1354, |
|
"carefully designed": 767, |
|
"designed enhance": 1492, |
|
"language processing enabling": 3249, |
|
"dataset compared baseline": 1355, |
|
"natural language processing enabling": 4184, |
|
"field natural language processing enabling": 2187, |
|
"complicated": 1019, |
|
"necessitate": 4205, |
|
"complex semantic": 1011, |
|
"compositional generalization": 1028, |
|
"using just": 6649, |
|
"impressive results": 2788, |
|
"distillation approach": 1616, |
|
"using knowledge": 6650, |
|
"models limitations": 3999 |
|
} |
|
} |
|
} |