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Cuiyun Gao

ACL 2026×2ICML 2026多模态强化学习与后训练推理安全可解释性
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0 一作 · 3 篇 · ACL 2026 / ICML 2026

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2026 顶会论文

3
作者位次 #5/7ACL 2026Poster· Natural Language Processing

Free Energy-Driven Reinforcement Learning with Adaptive Advantage Shaping for Unsupervised Reasoning in LLM s

Yiming Huang · Zhenbo Shi · Xin-Cheng Wen · Jichuan Zeng · Cuiyun Gao · Peiyi Han · Chuanyi Liu

摘要

Unsupervised reinforcement learning (RL) has emerged as a promising paradigm for enabling self-improvement in large language models (LLMs). However, existing unsupervised RL-based methods often lack the capacity to adapt to the model’s evolving reasoning capabilities during training. Therefore, t...

强化学习与后训练推理多模态OpenReview 项目页
作者位次 #4/6ACL 2026Findings· Findings of ACL

Adapt to Thrive! Adaptive Power-Mean Policy Optimization for Improved LLM Reasoning

Yiming Huang · Zhenbo Shi · Shuzheng Gao · Cuiyun Gao · Peiyi Han · Chuanyi Liu

摘要

Reinforcement Learning with Verifiable Rewards (RLVR) is an essential paradigm that enhances the reasoning capabilities of Large Language Models (LLMs). However, existing methods typically rely on static policy optimization schemes that misalign with the model’s evolving reasoning capabilities. T...

强化学习与后训练推理理论与学习动力学OpenReview 项目页

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