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Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 106 -
PaSa: An LLM Agent for Comprehensive Academic Paper Search
Paper • 2501.10120 • Published • 44 -
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong
Paper • 2501.09775 • Published • 29 -
ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario
Paper • 2501.10132 • Published • 19
Collections
Discover the best community collections!
Collections including paper arxiv:2501.18009
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Large Language Models Think Too Fast To Explore Effectively
Paper • 2501.18009 • Published • 23 -
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 108 -
Intuitive physics understanding emerges from self-supervised pretraining on natural videos
Paper • 2502.11831 • Published • 18 -
Cramming 1568 Tokens into a Single Vector and Back Again: Exploring the Limits of Embedding Space Capacity
Paper • 2502.13063 • Published • 66
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Large Language Models Think Too Fast To Explore Effectively
Paper • 2501.18009 • Published • 23 -
s1: Simple test-time scaling
Paper • 2501.19393 • Published • 111 -
Scalable-Softmax Is Superior for Attention
Paper • 2501.19399 • Published • 21 -
SoS1: O1 and R1-Like Reasoning LLMs are Sum-of-Square Solvers
Paper • 2502.20545 • Published • 20
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Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search
Paper • 2412.18319 • Published • 37 -
Token-Budget-Aware LLM Reasoning
Paper • 2412.18547 • Published • 46 -
Efficiently Serving LLM Reasoning Programs with Certaindex
Paper • 2412.20993 • Published • 36 -
B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners
Paper • 2412.17256 • Published • 46
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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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On Memorization of Large Language Models in Logical Reasoning
Paper • 2410.23123 • Published • 18 -
LLMs Do Not Think Step-by-step In Implicit Reasoning
Paper • 2411.15862 • Published • 10 -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 78 -
Deliberation in Latent Space via Differentiable Cache Augmentation
Paper • 2412.17747 • Published • 30
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PDFTriage: Question Answering over Long, Structured Documents
Paper • 2309.08872 • Published • 54 -
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 77 -
Table-GPT: Table-tuned GPT for Diverse Table Tasks
Paper • 2310.09263 • Published • 40 -
Context-Aware Meta-Learning
Paper • 2310.10971 • Published • 17
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Compression Represents Intelligence Linearly
Paper • 2404.09937 • Published • 27 -
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies
Paper • 2404.06395 • Published • 22 -
Long-context LLMs Struggle with Long In-context Learning
Paper • 2404.02060 • Published • 37 -
Are large language models superhuman chemists?
Paper • 2404.01475 • Published • 19