🔗 Who cites «Improving Alignment and Robustness with Circuit Breakers»

65 papers of our library cite it (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · ← back to «Improving Alignment and Robustness with Circuit Breakers»

1. AI Alignment: A Comprehensive SurveyarXiv:2310.19852Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.2023 · 173 citations
2. Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive AttacksarXiv:2404.02151Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion2024 · 118 citations
3. WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language ModelsConference on Neural Information Processing Systems (NeurIPS)Liwei Jiang, Kavel Rao, Seungju Han, et al.2024 · 92 citations
4. A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and BeyondarXiv:2503.21614Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.2025 · 55 citations
5. VLSBench: Unveiling Visual Leakage in Multimodal SafetyAnnual Meeting of the Association for Computational Linguistics (ACL)Xuhao Hu, Dongrui Liu, Hao Li, et al.2025 · 32 citations
6. The Hidden Risks of Large Reasoning Models: A Safety Assessment of R1International Joint Conference on Natural Language Processing (IJCNLP)Kaiwen Zhou, Chengzhi Liu, Xuandong Zhao, et al.2025 · 30 citations
7. Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red TeamingarXiv:2501.18837Mrinank Sharma, Meg Tong, Jesse Mu, et al.2025 · 29 citations
8. Refuse Whenever You Feel Unsafe: Improving Safety in LLMs via Decoupled Refusal TrainingAnnual Meeting of the Association for Computational Linguistics (ACL)Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.2025 · 19 citations
9. LLMs know their vulnerabilities: Uncover Safety Gaps through Natural Distribution ShiftsAnnual Meeting of the Association for Computational Linguistics (ACL)Qibing Ren, Hao Li, Dongrui Liu, et al.2025 · 18 citations
10. Safety Alignment via Constrained Knowledge UnlearningAnnual Meeting of the Association for Computational Linguistics (ACL)Zesheng Shi, Yucheng Zhou, Jing Li, et al.2025 · 13 citations
11. Layer-Aware Representation Filtering: Purifying Finetuning Data to Preserve LLM Safety AlignmentConference on Empirical Methods in Natural Language Processing (EMNLP)Hao Li, Lijun Li, Zhenghao Lu, et al.2025 · 11 citations
12. SafeKey: Amplifying Aha-Moment Insights for Safety ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Kaiwen Zhou, Xuandong Zhao, Jayanth Srinivasa, et al.2025 · 9 citations
13. HiddenGuard: Fine-Grained Safe Generation with Specialized Representation RouterAnnual Meeting of the Association for Computational Linguistics (ACL)Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.2026 · 4 citations
14. CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Biao Yi, Tiansheng Huang, Baolei Zhang, et al.2026 · 3 citations
15. Be Your Own Red Teamer: Safety Alignment via Self-Play and Reflective Experience ReplayFindings of the Association for Computational LinguisticsHao Wang, Yanting Wang, Hao Li, et al.2026 · 1 citation
16. Reasoning Up the Instruction Ladder for Controllable Language ModelsFindings of the Association for Computational LinguisticsZishuo Zheng, Vidhisha Balachandran, Chan Young Park, et al.2026 · 1 citation
17. Deactivating Refusal Triggers: Understanding and Mitigating Overrefusal in Safety AlignmentWorkshop on Trustworthy NLPZhiyu Xue, Zimo Qi, Guangliang Liu, et al.2026
18. Defeating Cerberus: Privacy-Leakage Mitigation in Vision Language ModelsFindings of the Association for Computational LinguisticsBoyang Zhang, Istemi Ekin Akkus, Ruichuan Chen, et al.2026
19. Preventing Safety Drift in Large Language Models via Coupled Weight and Activation ConstraintsFindings of the Association for Computational LinguisticsSongping Peng, Zhiheng Zhang, Daojian Zeng, et al.2026
20. Pruning Unsafe Tickets: A Resource-Efficient Framework for Safer and More Robust LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Wai Man Si, Mingjie Li, Michael Backes, et al.2026
21. Thinking Twice Makes Large Language Models Safer and More HelpfulFindings of the Association for Computational LinguisticsYutao Mou, Yuxiao Luo, Shikun Zhang, et al.2026

44 more papers of our library cite it; they have no page here yet.

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