🔗 Who cites «Shadow Alignment: The Ease of Subverting Safely-Aligned Language Models»

94 papers of our library cite it (of the 149,439 whose bibliographies we read) · 26 with a page here, the most cited first · ← back to «Shadow Alignment: The Ease of Subverting Safely-Aligned Language Models»

1. TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
2. Combating Misinformation in the Age of LLMs: Opportunities and ChallengesAI MagazineCanyu Chen, Kai Shu2023 · 214 citations
3. Refusal in Language Models Is Mediated by a Single DirectionarXiv:2406.11717Andy Arditi, Oscar Obeso, Aaquib Syed, et al.2024 · 196 citations
4. AI Alignment: A Comprehensive SurveyarXiv:2310.19852Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.2023 · 173 citations
5. MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language ModelsLecture notes in computer scienceXin Liu, Yichen Zhu, Jindong Gu, et al.2023 · 152 citations
6. The WMDP Benchmark: Measuring and Reducing Malicious Use With UnlearningarXiv:2403.03218Nathaniel Li, Alexander Pan, Anjali Gopal, et al.2024 · 127 citations
7. Safety Alignment Should Be Made More Than Just a Few Tokens DeeparXiv:2406.05946Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, et al.2024 · 97 citations
8. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
9. Survey of Vulnerabilities in Large Language Models Revealed by Adversarial AttacksarXiv:2310.10844Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.2023 · 83 citations
10. Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank ModificationsarXiv:2402.05162Boyi Wei, Kaixuan Huang, Yangsibo Huang, et al.2024 · 66 citations
11. A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and ToxicityarXiv:2401.01967Andrew Lee, Xiaoyan Bai, Itamar Pres, et al.2024 · 64 citations
12. Self-Distillation Bridges Distribution Gap in Language Model Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Zhaorui Yang, Tianyu Pang, Haozhe Feng, et al.2024 · 63 citations
13. Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task ArithmeticAnnual Meeting of the Association for Computational Linguistics (ACL)Rishabh Bhardwaj, Duc Anh Do, Soujanya Poria2024 · 59 citations
14. 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
15. Jailbreaking LLMs with Arabic Transliteration and ArabiziConference on Empirical Methods in Natural Language Processing (EMNLP)Mansour Al Ghanim, Saleh Almohaimeed, Mengxin Zheng, et al.2024 · 16 citations
16. Beware of Your Po! Measuring and Mitigating AI Safety Risks in Role-Play Fine-Tuning of LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Weixiang Zhao, Yulin Hu, Yang Deng, et al.2025 · 9 citations
17. The Dark Side of Function Calling: Pathways to Jailbreaking Large Language ModelsInternational Conference on Computational Linguistics (COLING)Zihui Wu, Haichang Gao, Jianping He, et al.2025 · 8 citations
18. 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
19. 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
20. 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
21. Measuring Human Contribution in AI-Assisted Content GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Yueqi Xie, Tao Qi, Jingwei Yi, et al.2026 · 1 citation
22. CSULoRA: Closest Safe Update Low-Rank AdaptationInternational Conference on Natural Language Processing and Artificial Intelligence for Cyber SecurityOleksandr Marchenko, Adelaide Danilov, Aria Nourbakhsh, et al.2026
23. OASIS: Mitigating Harmful Fine-tuning Attacks on LLMs via Orthogonal and Adaptive Safety Alignment StrategyAnnual Meeting of the Association for Computational Linguistics (ACL)Jiayu Tang, Guowei Peng, Qiuhao Xie, et al.2026
24. Probing the Plasticity and Correlation of LLM Value Systems: LLM Value Rankings are Not StableFindings of the Association for Computational LinguisticsZhenheng Tang, Qihua Pan, Jingya Shen, et al.2026
25. Safeguarding LLM Fine-tuning via Push-Pull Distributional AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Haozhong Wang, Zhuo Li, Yibo Yang, et al.2026
26. The Art of (Mis)alignment: How Fine-Tuning Methods Effectively Misalign and Realign LLMs in Post-TrainingFindings of the Association for Computational LinguisticsRui Zhang, Hongwei Li, Yun Shen, et al.2026

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