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Internal Consistency and Self-Feedback in Large Language Models: A Survey
Paper • 2407.14507 • Published • 46 -
Large Language Models are Zero-Shot Reasoners
Paper • 2205.11916 • Published • 1 -
Let's Verify Step by Step
Paper • 2305.20050 • Published • 10 -
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Paper • 2201.11903 • Published • 11
Collections
Discover the best community collections!
Collections including paper arxiv:2502.06807
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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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Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 106 -
PaSa: An LLM Agent for Comprehensive Academic Paper Search
Paper • 2501.10120 • Published • 43 -
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
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Competitive Programming with Large Reasoning Models
Paper • 2502.06807 • Published • 67 -
Search-o1: Agentic Search-Enhanced Large Reasoning Models
Paper • 2501.05366 • Published • 95 -
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models
Paper • 2501.09686 • Published • 37 -
Reasoning Language Models: A Blueprint
Paper • 2501.11223 • Published • 32
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Evaluation of OpenAI o1: Opportunities and Challenges of AGI
Paper • 2409.18486 • Published -
An Open Recipe: Adapting Language-Specific LLMs to a Reasoning Model in One Day via Model Merging
Paper • 2502.09056 • Published • 30 -
Competitive Programming with Large Reasoning Models
Paper • 2502.06807 • Published • 67
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CMoE: Fast Carving of Mixture-of-Experts for Efficient LLM Inference
Paper • 2502.04416 • Published • 12 -
Competitive Programming with Large Reasoning Models
Paper • 2502.06807 • Published • 67 -
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling
Paper • 2502.06703 • Published • 142
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Competitive Programming with Large Reasoning Models
Paper • 2502.06807 • Published • 67 -
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling
Paper • 2502.06703 • Published • 142 -
Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning
Paper • 2502.06781 • Published • 60 -
LIMO: Less is More for Reasoning
Paper • 2502.03387 • Published • 57
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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 • 83 -
VideoWorld: Exploring Knowledge Learning from Unlabeled Videos
Paper • 2501.09781 • Published • 26