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Rongyu Cao

ACL 2026×2AAAI 2026推理强化学习与后训练理论与学习动力学评测与基准社会与人本
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0 一作 · 3 篇 · ACL 2026 / AAAI 2026

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2026 顶会论文

3
作者位次 #7/14ACL 2026Poster· Natural Language Processing

RL - PLUS : Countering Capability Boundary Collapse of LLM s in Reinforcement Learning with Hybrid-policy Optimization

Yihong Dong · Xue Jiang · Yongding Tao · Huanyu Liu · Kechi Zhang · Lili Mou · Rongyu Cao · YINGWEI MA · Jue Chen · Binhua Li · Zhi Jin · Fei Huang · Yongbin Li · Ge Li

摘要

Reinforcement Learning with Verifiable Reward (RLVR) has significantly advanced the complex reasoning abilities of Large Language Models (LLMs). However, it struggles to break through the inherent capability boundaries of the base LLM, due to its essentially on-policy strategy coupled with LLM’s...

强化学习与后训练推理理论与学习动力学OpenReview 项目页
作者位次 #3/10ACL 2026Findings· Findings of ACL

Format-Adapter: Improving Reasoning Capability of LLM s by Adapting Suitable Format

Dingzirui Wang · Xuanliang Zhang · Rongyu Cao · Longxu Dou · Xianzhen Luo · YINGWEI MA · Qingfu Zhu · Binhua Li · Fei Huang · Yongbin Li

摘要

Generating and voting multiple answers is an effective method to mitigate reasoning inconsistencies of large language models (LLMs). Prior works have shown that multiple reasoning formats outperform a single format when generating multiple answers. However, previous works using multiple formats r...

推理评测与基准社会与人本OpenReview 项目页

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