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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 24 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 152 -
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:2504.16030
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Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers
Paper • 2506.23918 • Published • 90 -
LiveCC: Learning Video LLM with Streaming Speech Transcription at Scale
Paper • 2504.16030 • Published • 36 -
Time Blindness: Why Video-Language Models Can't See What Humans Can?
Paper • 2505.24867 • Published • 82 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 251
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RuCCoD: Towards Automated ICD Coding in Russian
Paper • 2502.21263 • Published • 133 -
Unified Reward Model for Multimodal Understanding and Generation
Paper • 2503.05236 • Published • 123 -
Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching
Paper • 2503.05179 • Published • 46 -
R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
Paper • 2503.05592 • Published • 27
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 15 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23
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Human-inspired Perspectives: A Survey on AI Long-term Memory
Paper • 2411.00489 • Published • 1 -
Multimodal Fusion with LLMs for Engagement Prediction in Natural Conversation
Paper • 2409.09135 • Published • 2 -
Reading Recognition in the Wild
Paper • 2505.24848 • Published • 1 -
EgoLife: Towards Egocentric Life Assistant
Paper • 2503.03803 • Published • 46
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iVideoGPT: Interactive VideoGPTs are Scalable World Models
Paper • 2405.15223 • Published • 17 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 55 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 90 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 34
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DocGraphLM: Documental Graph Language Model for Information Extraction
Paper • 2401.02823 • Published • 36 -
Understanding LLMs: A Comprehensive Overview from Training to Inference
Paper • 2401.02038 • Published • 65 -
DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 189 -
Attention Where It Matters: Rethinking Visual Document Understanding with Selective Region Concentration
Paper • 2309.01131 • Published • 1
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 24 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 152 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
-
Human-inspired Perspectives: A Survey on AI Long-term Memory
Paper • 2411.00489 • Published • 1 -
Multimodal Fusion with LLMs for Engagement Prediction in Natural Conversation
Paper • 2409.09135 • Published • 2 -
Reading Recognition in the Wild
Paper • 2505.24848 • Published • 1 -
EgoLife: Towards Egocentric Life Assistant
Paper • 2503.03803 • Published • 46
-
Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers
Paper • 2506.23918 • Published • 90 -
LiveCC: Learning Video LLM with Streaming Speech Transcription at Scale
Paper • 2504.16030 • Published • 36 -
Time Blindness: Why Video-Language Models Can't See What Humans Can?
Paper • 2505.24867 • Published • 82 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 251
-
RuCCoD: Towards Automated ICD Coding in Russian
Paper • 2502.21263 • Published • 133 -
Unified Reward Model for Multimodal Understanding and Generation
Paper • 2503.05236 • Published • 123 -
Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching
Paper • 2503.05179 • Published • 46 -
R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
Paper • 2503.05592 • Published • 27
-
iVideoGPT: Interactive VideoGPTs are Scalable World Models
Paper • 2405.15223 • Published • 17 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 55 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 90 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 34
-
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 15 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23
-
DocGraphLM: Documental Graph Language Model for Information Extraction
Paper • 2401.02823 • Published • 36 -
Understanding LLMs: A Comprehensive Overview from Training to Inference
Paper • 2401.02038 • Published • 65 -
DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 189 -
Attention Where It Matters: Rethinking Visual Document Understanding with Selective Region Concentration
Paper • 2309.01131 • Published • 1