Zhanke Zhou

Co-rewarding: Stable Self-supervised RL for Eliciting Reasoning in Large Language Models

Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models

Reference-guided Policy Optimization for Molecular Optimization via LLM Reasoning

CoDaPO: Confidence and Difficulty-Adaptive Policy Optimization for Language Models

Observe-Then-Think: Learning to Elicit Multimodal Understanding by Decoupling Perception and Reasoning

RewardFlow: Propagating Reward in the State Graphs of Agentic Learning with LLMs

VeriBench: End-to-End Formal Verification Benchmark for AI Code Generation in Lean 4

From Debate to Equilibrium: Belief‑Driven Multi‑Agent LLM Reasoning via Bayesian Nash Equilibrium

Noisy Test-Time Adaptation in Vision-Language Models

Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond

Breaking the Detection-Generalization Paradox on Out-Of-Distribution Data

Towards Efficient and Scalable Multi-agent Reasoning via Bayesian Nash Equilibrium

From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information?

Nested Gloss Makes Large Language Models Lost