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Chenfu Bao

ACL 2026×2ICLR 2026强化学习与后训练检索与知识可解释性对齐与偏好安全
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0 一作 · 3 篇 · ACL 2026 / ICLR 2026

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2026 顶会论文

3
作者位次 #7/8ACL 2026Poster· Natural Language Processing

Safety-Utility Conflicts Are Not Global: Surgical Alignment via Head-Level Diagnosis

Wang Cai · Yilin Wen · Jinchang Hou · Du Su · Guoqiu Wang · Zhonghou Lv · Chenfu Bao · Yunfang Wu

摘要

Safety alignment in Large Language Models (LLMs) inherently presents a multi-objective optimization conflict, often accompanied by an unintended degradation of general capabilities. Existing mitigation strategies typically rely on global gradient geometry to resolve these conflicts, yet they over...

可解释性对齐与偏好安全OpenReview 项目页
作者位次 #8/8ACL 2026Poster· Natural Language Processing

Token-Level Policy Optimization: Linking Group-Level Rewards to Token-Level Aggregation via sequence-level likelihood

Xingyu Lin · Yilin Wen · Du Su · En Wang · Wenbin Liu · Zhonghou Lv · Jinchang Hou · Chenfu Bao

摘要

Group Relative Policy Optimization (GRPO) has significantly advanced the reasoning ability of large language models (LLMs), particularly in their mathemat- ical reasoning performance. However, GRPO and related entropy regularization methods still struggle with token-level sparse-rewards, which is...

推理强化学习与后训练评测与基准OpenReview 项目页

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