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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 22 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 82 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 145 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2406.07230
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iVideoGPT: Interactive VideoGPTs are Scalable World Models
Paper • 2405.15223 • Published • 12 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 53 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 87 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 31
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Flowing from Words to Pixels: A Framework for Cross-Modality Evolution
Paper • 2412.15213 • Published • 25 -
No More Adam: Learning Rate Scaling at Initialization is All You Need
Paper • 2412.11768 • Published • 41 -
Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference
Paper • 2412.13663 • Published • 117 -
Autoregressive Video Generation without Vector Quantization
Paper • 2412.14169 • Published • 14
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Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 104 -
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
Paper • 2404.12253 • Published • 54 -
Make Your LLM Fully Utilize the Context
Paper • 2404.16811 • Published • 52 -
ReFT: Representation Finetuning for Language Models
Paper • 2404.03592 • Published • 91
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MMDU: A Multi-Turn Multi-Image Dialog Understanding Benchmark and Instruction-Tuning Dataset for LVLMs
Paper • 2406.11833 • Published • 61 -
Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models
Paper • 2406.11230 • Published • 33 -
Two Giraffes in a Dirt Field: Using Game Play to Investigate Situation Modelling in Large Multimodal Models
Paper • 2406.14035 • Published • 12 -
Needle In A Multimodal Haystack
Paper • 2406.07230 • Published • 53
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BLINK: Multimodal Large Language Models Can See but Not Perceive
Paper • 2404.12390 • Published • 24 -
SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension
Paper • 2404.16790 • Published • 7 -
Plot2Code: A Comprehensive Benchmark for Evaluating Multi-modal Large Language Models in Code Generation from Scientific Plots
Paper • 2405.07990 • Published • 16 -
MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding
Paper • 2406.09411 • Published • 18
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BLINK: Multimodal Large Language Models Can See but Not Perceive
Paper • 2404.12390 • Published • 24 -
TextSquare: Scaling up Text-Centric Visual Instruction Tuning
Paper • 2404.12803 • Published • 29 -
Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models
Paper • 2404.13013 • Published • 30 -
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD
Paper • 2404.06512 • Published • 29
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GAIA: a benchmark for General AI Assistants
Paper • 2311.12983 • Published • 187 -
MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
Paper • 2311.16502 • Published • 35 -
BLINK: Multimodal Large Language Models Can See but Not Perceive
Paper • 2404.12390 • Published • 24 -
RULER: What's the Real Context Size of Your Long-Context Language Models?
Paper • 2404.06654 • Published • 34
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 25 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 12 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 40 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 20
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PsiPi/liuhaotian_llava-v1.5-13b-GGUF
Image-Text-to-Text • Updated • 812 • 36 -
TRI-ML/prismatic-vlms
Image-to-Text • Updated • 16 -
bczhou/tiny-llava-v1-hf
Image-Text-to-Text • Updated • 1.35k • 56 -
ViGoR: Improving Visual Grounding of Large Vision Language Models with Fine-Grained Reward Modeling
Paper • 2402.06118 • Published • 13