readme updated
Browse files
README.md
CHANGED
@@ -8,11 +8,12 @@ It thinks like o1
|
|
8 |
[ ] Better error handling
|
9 |
[ ] Add Tools (web, math, code)
|
10 |
[ ] Make cli
|
11 |
-
|
12 |
|
13 |
## What it does
|
14 |
|
15 |
-
- It
|
|
|
16 |
|
17 |
## Installation
|
18 |
|
@@ -28,10 +29,31 @@ HAVE FUN.
|
|
28 |
|
29 |
## Helpful Papers
|
30 |
|
31 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
32 |
|
33 |
2. The Impact of Reasoning Step Length on Large Language Models
|
34 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
35 |
3. Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters [2212.10001](https://arxiv.org/abs/2212.10001)
|
36 |
```bibtex
|
37 |
@misc{wang2023understandingchainofthoughtpromptingempirical,
|
@@ -43,4 +65,8 @@ HAVE FUN.
|
|
43 |
primaryClass={cs.CL},
|
44 |
url={https://arxiv.org/abs/2212.10001},
|
45 |
}
|
46 |
-
```
|
|
|
|
|
|
|
|
|
|
8 |
[ ] Better error handling
|
9 |
[ ] Add Tools (web, math, code)
|
10 |
[ ] Make cli
|
11 |
+
[ ] better prompts for mathematical reasoning/reviewing
|
12 |
|
13 |
## What it does
|
14 |
|
15 |
+
- It taks the prompt, decides whether to use chain of thought or direct answer, if cot then generates answer and does self review, if direct answer then directly generates answer.
|
16 |
+
- Mathematical reasoning, symbolic reasoning and semi-symbolic reasoning kind of tasks generally improves with chain of thought, but direct answer is good for factual recall, simple inferences, commonsense reasoning, language understanding tasks.
|
17 |
|
18 |
## Installation
|
19 |
|
|
|
29 |
|
30 |
## Helpful Papers
|
31 |
|
32 |
+
1. To Cot or not to Cot? CHAIN-OF-THOUGHT HELPS MAINLY ON MATH AND SYMBOLIC REASONING
|
33 |
+
```bibtex
|
34 |
+
@misc{sprague2024cotcotchainofthoughthelps,
|
35 |
+
title={To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning},
|
36 |
+
author={Zayne Sprague and Fangcong Yin and Juan Diego Rodriguez and Dongwei Jiang and Manya Wadhwa and Prasann Singhal and Xinyu Zhao and Xi Ye and Kyle Mahowald and Greg Durrett},
|
37 |
+
year={2024},
|
38 |
+
eprint={2409.12183},
|
39 |
+
archivePrefix={arXiv},
|
40 |
+
primaryClass={cs.CL},
|
41 |
+
url={https://arxiv.org/abs/2409.12183},
|
42 |
+
}
|
43 |
+
```
|
44 |
|
45 |
2. The Impact of Reasoning Step Length on Large Language Models
|
46 |
+
```bibtex
|
47 |
+
@misc{jin2024impactreasoningsteplength,
|
48 |
+
title={The Impact of Reasoning Step Length on Large Language Models},
|
49 |
+
author={Mingyu Jin and Qinkai Yu and Dong Shu and Haiyan Zhao and Wenyue Hua and Yanda Meng and Yongfeng Zhang and Mengnan Du},
|
50 |
+
year={2024},
|
51 |
+
eprint={2401.04925},
|
52 |
+
archivePrefix={arXiv},
|
53 |
+
primaryClass={cs.CL},
|
54 |
+
url={https://arxiv.org/abs/2401.04925},
|
55 |
+
}
|
56 |
+
```
|
57 |
3. Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters [2212.10001](https://arxiv.org/abs/2212.10001)
|
58 |
```bibtex
|
59 |
@misc{wang2023understandingchainofthoughtpromptingempirical,
|
|
|
65 |
primaryClass={cs.CL},
|
66 |
url={https://arxiv.org/abs/2212.10001},
|
67 |
}
|
68 |
+
```
|
69 |
+
|
70 |
+
# But me a Coffee
|
71 |
+
|
72 |
+
[!["Buy Me A Coffee"](https://www.buymeacoffee.com/assets/img/custom_images/orange_img.png)](https://buymeacoffee.com/tikendraw)
|