Who cites Xun Zhao
- TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
- Combating Misinformation in the Age of LLMs: Opportunities and ChallengesAI MagazineCanyu Chen, Kai Shu2023 · 214 citations
- Refusal in Language Models Is Mediated by a Single DirectionarXiv:2406.11717Andy Arditi, Oscar Obeso, Aaquib Syed, et al.2024 · 196 citations
- AI Alignment: A Comprehensive SurveyarXiv:2310.19852Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.2023 · 173 citations
- 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
- The WMDP Benchmark: Measuring and Reducing Malicious Use With UnlearningarXiv:2403.03218Nathaniel Li, Alexander Pan, Anjali Gopal, et al.2024 · 127 citations
- Safety Alignment Should Be Made More Than Just a Few Tokens DeeparXiv:2406.05946Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, et al.2024 · 97 citations
- Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
- 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
- Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank ModificationsarXiv:2402.05162Boyi Wei, Kaixuan Huang, Yangsibo Huang, et al.2024 · 66 citations
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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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