🔗 Who cites «Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications»

64 papers of our library cite it (of the 149,439 whose bibliographies we read) · 17 with a page here, the most cited first · ← back to «Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications»

1. Refusal in Language Models Is Mediated by a Single DirectionarXiv:2406.11717Andy Arditi, Oscar Obeso, Aaquib Syed, et al.2024 · 196 citations
2. Safety Alignment Should Be Made More Than Just a Few Tokens DeeparXiv:2406.05946Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, et al.2024 · 97 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. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
5. Understanding Jailbreak Success: A Study of Latent Space Dynamics in Large Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Sarah Ball, Frauke Kreuter, Nina Panickssery2026 · 17 citations
6. 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
7. Rethinking Jailbreak Detection of Large Vision Language Models with Representational Contrastive ScoringAnnual Meeting of the Association for Computational Linguistics (ACL)Peichun Hua, Hao Li, Shanghao Shi, et al.2026 · 10 citations
8. LED-Merging: Mitigating Safety-Utility Conflicts in Model Merging with Location-Election-DisjointAnnual Meeting of the Association for Computational Linguistics (ACL)Qianli Ma, Dongrui Liu, Qian Chen, et al.2025 · 5 citations
9. Why LLM Safety Guardrails Collapse After Fine-tuning: A Similarity Analysis Between Alignment and Fine-tuning DatasetsAnnual Meeting of the Association for Computational Linguistics (ACL)Lei Hsiung, Tianyu Pang, Yung-Chen Tang, et al.2026 · 4 citations
10. SDD: Self-Degraded Defense against Malicious Fine-tuningAnnual Meeting of the Association for Computational Linguistics (ACL)ZiXuan Chen, Weikai Lu, Xin Lin, et al.2025 · 4 citations
11. 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
12. Unraveling LLM Jailbreaks Through Safety Knowledge NeuronsConference of the European Chapter of the Association for Computational Linguistics (EACL)Chongwen Zhao, Yutong Ke, Kaizhu Huang2026 · 3 citations
13. SafeConstellations: Mitigating Over-Refusals in LLMs Through Task-Aware Representation SteeringAnnual Meeting of the Association for Computational Linguistics (ACL)Utsav Maskey, Sumit Yadav, Mark Dras, et al.2026 · 1 citation
14. How Do LLMs and VLMs Understand Viewpoint Rotation Without Vision? An Interpretability StudyAnnual Meeting of the Association for Computational Linguistics (ACL)Zhen Yang, Ping Jian, Zhongbin Guo, et al.2026
15. Interpretable Safety Alignment via SAE-Constructed Low-Rank Subspace AdaptationAnnual Meeting of the Association for Computational Linguistics (ACL)Dianyun Wang, Qingsen Ma, Yuhu Shang, et al.2026
16. 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
17. 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

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