Dian Yu

DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning

Vision-SR1: Self-Rewarding Vision-Language Model via Reasoning Decomposition and Multi-Reward Policy Optimization

CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models

On the Evolution of Language Models without Labels: Majority Drives Selection, Novelty Promotes Variation

VOGUE: Guiding Exploration with Visual Uncertainty Improves Multimodal Reasoning

One Token to Fool LLM-as-a-Judge

CLUE: Non-parametric Verification from Experience via Hidden-State Clustering

Thoughts Are All Over the Place: On the Underthinking of Long Reasoning Models

Improving LLM General Preference Alignment via Optimistic Online Mirror Descent

DOTS: Learning to Reason Dynamically in LLMs via Optimal Reasoning Trajectories Search

Iterative Nash Policy Optimization: Aligning LLMs with General Preferences via No-Regret Learning

Do NOT Think That Much for 2+3=? On the Overthinking of Long Reasoning Models

Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs

SIaM: Self-Improving Code-Assisted Mathematical Reasoning of Large Language Models