Large Language Models Can Self-Improve in Long-context Reasoning
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2411.08147
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Published
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64
reasoning
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Reverse Thinking Makes LLMs Stronger Reasoners
Paper • 2411.19865 • Published • 21 -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 78 -
HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs
Paper • 2412.18925 • Published • 97 -
ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning
Paper • 2501.06590 • Published • 9 -
O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning
Paper • 2501.12570 • Published • 24 -
Pairwise RM: Perform Best-of-N Sampling with Knockout Tournament
Paper • 2501.13007 • Published • 20 -
Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training
Paper • 2501.11425 • Published • 91 -
Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback
Paper • 2501.10799 • Published • 15 -
Process Reinforcement through Implicit Rewards
Paper • 2502.01456 • Published • 54 -
One Example Shown, Many Concepts Known! Counterexample-Driven Conceptual Reasoning in Mathematical LLMs
Paper • 2502.10454 • Published • 6 -
Large Language Models and Mathematical Reasoning Failures
Paper • 2502.11574 • Published • 3 -
PhysReason: A Comprehensive Benchmark towards Physics-Based Reasoning
Paper • 2502.12054 • Published • 5