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

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) 2026 Open access

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Authors: 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
DOI: 10.18653/v1/2026.acl-long.936
Cited by: 0

Abstract

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. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

Fields of Study & Subjects

Semantic Web and Ontologies Bayesian Modeling and Causal Inference AI-based Problem Solving and Planning

Publication details

Journal / source
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Publisher
Association for Computational Linguistics
Pages
20438–20457
Publication date
1 January 2026
Language
EN