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Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 93 -
PaSa: An LLM Agent for Comprehensive Academic Paper Search
Paper • 2501.10120 • Published • 37 -
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong
Paper • 2501.09775 • Published • 26 -
VideoWorld: Exploring Knowledge Learning from Unlabeled Videos
Paper • 2501.09781 • Published • 20
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Collections including paper arxiv:2501.09781
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Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model
Paper • 2407.07053 • Published • 43 -
LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models
Paper • 2407.12772 • Published • 34 -
VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models
Paper • 2407.11691 • Published • 14 -
MMIU: Multimodal Multi-image Understanding for Evaluating Large Vision-Language Models
Paper • 2408.02718 • Published • 61
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rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
Paper • 2501.04519 • Published • 244 -
Learning an evolved mixture model for task-free continual learning
Paper • 2207.05080 • Published • 1 -
EVOLvE: Evaluating and Optimizing LLMs For Exploration
Paper • 2410.06238 • Published • 1 -
Smaller Language Models Are Better Instruction Evolvers
Paper • 2412.11231 • Published • 27
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Video Creation by Demonstration
Paper • 2412.09551 • Published • 8 -
DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation
Paper • 2412.07589 • Published • 45 -
Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation
Paper • 2412.06531 • Published • 71 -
APOLLO: SGD-like Memory, AdamW-level Performance
Paper • 2412.05270 • Published • 38
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Scaling Law with Learning Rate Annealing
Paper • 2408.11029 • Published • 3 -
Token Turing Machines
Paper • 2211.09119 • Published • 1 -
VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
Paper • 2203.12602 • Published -
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design
Paper • 2305.13035 • Published
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Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset
Paper • 2403.09029 • Published • 55 -
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
Paper • 2403.12968 • Published • 25 -
RAFT: Adapting Language Model to Domain Specific RAG
Paper • 2403.10131 • Published • 69 -
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
Paper • 2403.09629 • Published • 76
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 26 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 13 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 41 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 22