On Memorization of Large Language Models in Logical Reasoning
Paper
• 2410.23123 • Published
• 18
Reasoning
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LLMs Do Not Think Step-by-step In Implicit Reasoning
Paper • 2411.15862 • Published • 9 -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 94 -
Deliberation in Latent Space via Differentiable Cache Augmentation
Paper • 2412.17747 • Published • 32 -
Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces
Paper • 2412.14171 • Published • 24 -
Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs
Paper • 2412.21187 • Published • 40 -
Test-time Computing: from System-1 Thinking to System-2 Thinking
Paper • 2501.02497 • Published • 45 -
rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
Paper • 2501.04519 • Published • 288 -
Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Though
Paper • 2501.04682 • Published • 99 -
Search-o1: Agentic Search-Enhanced Large Reasoning Models
Paper • 2501.05366 • Published • 102 -
Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 115 -
Reasoning Language Models: A Blueprint
Paper • 2501.11223 • Published • 33 -
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Paper • 2501.12948 • Published • 441 -
O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning
Paper • 2501.12570 • Published • 28 -
Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs
Paper • 2501.18585 • Published • 61 -
Large Language Models Think Too Fast To Explore Effectively
Paper • 2501.18009 • Published • 23 -
s1: Simple test-time scaling
Paper • 2501.19393 • Published • 124 -
LIMO: Less is More for Reasoning
Paper • 2502.03387 • Published • 62 -
Demystifying Long Chain-of-Thought Reasoning in LLMs
Paper • 2502.03373 • Published • 58 -
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling
Paper • 2502.06703 • Published • 152 -
LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!
Paper • 2502.07374 • Published • 40 -
Logical Reasoning in Large Language Models: A Survey
Paper • 2502.09100 • Published • 24 -
Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models
Paper • 2503.16419 • Published • 77 -
Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn't
Paper • 2503.16219 • Published • 52 -
Reasoning to Learn from Latent Thoughts
Paper • 2503.18866 • Published • 13 -
System-1.5 Reasoning: Traversal in Language and Latent Spaces with Dynamic Shortcuts
Paper • 2505.18962 • Published • 12 -
Thinking Sparks!: Emergent Attention Heads in Reasoning Models During Post Training
Paper • 2509.25758 • Published • 23 -
Supervised Reinforcement Learning: From Expert Trajectories to Step-wise Reasoning
Paper • 2510.25992 • Published • 48 -
Cognitive Foundations for Reasoning and Their Manifestation in LLMs
Paper • 2511.16660 • Published • 11 -
State over Tokens: Characterizing the Role of Reasoning Tokens
Paper • 2512.12777 • Published • 5 -
When Reasoning Meets Its Laws
Paper • 2512.17901 • Published • 61 -
Golden Goose: A Simple Trick to Synthesize Unlimited RLVR Tasks from Unverifiable Internet Text
Paper • 2601.22975 • Published • 109 -
Does Your Reasoning Model Implicitly Know When to Stop Thinking?
Paper • 2602.08354 • Published • 261