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Collections including paper arxiv:2501.06252
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Dolphin: Closed-loop Open-ended Auto-research through Thinking, Practice, and Feedback
Paper • 2501.03916 • Published • 15 -
Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Though
Paper • 2501.04682 • Published • 91 -
Agent Laboratory: Using LLM Agents as Research Assistants
Paper • 2501.04227 • Published • 86 -
Search-o1: Agentic Search-Enhanced Large Reasoning Models
Paper • 2501.05366 • Published • 95
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rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
Paper • 2501.04519 • Published • 263 -
Transformer^2: Self-adaptive LLMs
Paper • 2501.06252 • Published • 53 -
Multimodal LLMs Can Reason about Aesthetics in Zero-Shot
Paper • 2501.09012 • Published • 10 -
FAST: Efficient Action Tokenization for Vision-Language-Action Models
Paper • 2501.09747 • Published • 23
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2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 100 -
CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings
Paper • 2501.01257 • Published • 50 -
Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models
Paper • 2501.01423 • Published • 37 -
REDUCIO! Generating 1024times1024 Video within 16 Seconds using Extremely Compressed Motion Latents
Paper • 2411.13552 • Published
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MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models
Paper • 2501.02955 • Published • 40 -
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 100 -
MMVU: Measuring Expert-Level Multi-Discipline Video Understanding
Paper • 2501.12380 • Published • 84 -
VideoWorld: Exploring Knowledge Learning from Unlabeled Videos
Paper • 2501.09781 • Published • 27
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Transformer^2: Self-adaptive LLMs
Paper • 2501.06252 • Published • 53 -
s1: Simple test-time scaling
Paper • 2501.19393 • Published • 111 -
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling
Paper • 2502.06703 • Published • 142 -
Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models
Paper • 2501.12370 • Published • 11