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Junxiao Yang

ACL 2026×2ICLR 2026×2AAAI 2026安全社会与人本推理强化学习与后训练可解释性
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2 一作 · 5 篇 · ACL 2026 / ICLR 2026 / AAAI 2026

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2026 顶会论文

5
作者位次 #4/11ACL 2026Poster· Natural Language Processing

How Should We Enhance the Safety of Large Reasoning Models: An Empirical Study

Zhexin Zhang · Xian Qi Loye · Victor Shea-Jay Huang · Junxiao Yang · Qi Zhu · Shiyao Cui · Fei Mi · Lifeng Shang · Yingkang Wang · Hongning Wang · Minlie Huang

摘要

Large Reasoning Models (LRMs) have achieved remarkable success on reasoning-intensive tasks such as mathematics and programming. However, their enhanced reasoning capabilities do not necessarily translate to improved safety performance—and in some cases, may even degrade it. This raises an import...

推理强化学习与后训练安全OpenReview 项目页
一作ACL 2026Poster· Natural Language Processing

LASA : Language-Agnostic Semantic Alignment at the Semantic Bottleneck for LLM Safety

Junxiao Yang · Haoran Liu · Jinzhe Tu · Jiale Cheng · Zhexin Zhang · Shiyao Cui · Jiaqi Weng · Jialing Tao · Hui Xue · Hongning Wang · Han Qiu · Minlie Huang

摘要

Large language models (LLMs) have demonstrated better safety performance in high-resource languages than in low-resource languages. We attribute this issue as a mismatch gap between language-agnostic semantic understanding ability and language dominant safety alignment biased toward high-resource...

安全对齐与偏好可解释性OpenReview 项目页

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