🧑‍🔬 Who cites Chirag Agarwal

94 citations of their works from 94 papers of our library (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · ← Chirag Agarwal

1. Survey of Hallucination in Natural Language GenerationACM Computing SurveysZiwei Ji, Nayeon Lee, Rita Frieske, et al.2022 · 5,974 citations
2. Security and Privacy Challenges of Large Language Models: A SurveyACM Computing SurveysBadhan Chandra Das, M. Hadi Amini, Yanzhao Wu2024 · 424 citations
3. JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Patrick Chao, Edoardo Debenedetti, Alexander Robey, et al.2024 · 277 citations
4. Aya Model: An Instruction Finetuned Open-Access Multilingual Language ModelarXiv:2402.07827Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.2024 · 253 citations
5. TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
6. How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Yi Zeng, Hongpeng Lin, Jingwen Zhang, et al.2024 · 203 citations
7. SmoothLLM: Defending Large Language Models Against Jailbreaking AttacksarXiv:2310.03684Alexander Robey, Eric Wong, Hamed Hassani, et al.2023 · 164 citations
8. Jailbreak and Guard Aligned Language Models with Only Few In-Context DemonstrationsarXiv:2310.06387Zeming Wei, Yifei Wang, Ang Li, et al.2023 · 130 citations
9. SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language ModelsFindings of the Association for Computational LinguisticsLijun Li, Bowen Dong, Ruohui Wang, et al.2024 · 119 citations
10. Defending Against Alignment-Breaking Attacks via Robustly Aligned LLMAnnual Meeting of the Association for Computational Linguistics (ACL)Bochuan Cao, Yuanpu Cao, Lu Lin, et al.2024 · 109 citations
11. Is LLM-as-a-Judge Robust? Investigating Universal Adversarial Attacks on Zero-shot LLM AssessmentConference on Empirical Methods in Natural Language Processing (EMNLP)Vyas Raina, Adian Liusie, Mark Gales2024 · 86 citations
12. 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
13. Reasoning-to-Defend: Safety-Aware Reasoning Can Defend Large Language Models from JailbreakingConference on Empirical Methods in Natural Language Processing (EMNLP)Junda Zhu, Lingyong Yan, Shuaiqiang Wang, et al.2025 · 21 citations
14. from Benign import Toxic: Jailbreaking the Language Model via Adversarial MetaphorsAnnual Meeting of the Association for Computational Linguistics (ACL)Yu Yan, Sheng Sun, Zenghao Duan, et al.2025 · 12 citations
15. 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
16. 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
17. Calibrating Inference Time Alignment with Sequence-level Risk AccumulationAnnual Meeting of the Association for Computational Linguistics (ACL)Shanwen Tan, Ziyang Dong, Wei Ju, et al.2026
18. Towards Understanding the Robustness of Sparse AutoencodersFindings of the Association for Computational LinguisticsAhson Saiyed, Sabrina Sadiekh, Chirag Agarwal2026

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