🧑‍🔬 Who cites Arvind Narayanan

226 citations of their works from 183 papers of our library (of the 149,439 whose bibliographies we read) · 26 with a page here, the most cited first · ← Arvind Narayanan

1. 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
2. Hallucination-Free? Assessing the Reliability of Leading AI Legal Research ToolsarXiv:2405.20362Varun Magesh, Faiz Surani, Matthew Dahl, et al.2024 · 271 citations
3. SmoothLLM: Defending Large Language Models Against Jailbreaking AttacksarXiv:2310.03684Alexander Robey, Eric Wong, Hamed Hassani, et al.2023 · 164 citations
4. MLE-bench: Evaluating Machine Learning Agents on Machine Learning EngineeringarXiv:2410.07095Jun Shern Chan, Neil Chowdhury, Oliver Jaffe, et al.2024 · 140 citations
5. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
6. 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
7. Why Do Multi-Agent LLM Systems Fail?arXiv:2503.13657Mert Cemri, Melissa Z. Pan, Shuyi Yang, et al.2025 · 89 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. PaperBench: Evaluating AI's Ability to Replicate AI ResearcharXiv:2504.01848Giulio Starace, Oliver Jaffe, Dane Sherburn, et al.2025 · 86 citations
10. More Agents Is All You NeedarXiv:2402.05120Junyou Li, Qin Zhang, Yangbin Yu, et al.2024 · 85 citations
11. ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific DiscoveryarXiv:2410.05080Ziru Chen, Shijie Chen, Yuting Ning, et al.2024 · 81 citations
12. BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical TextarXiv:2403.18421Elliot Bolton, Abhinav Venigalla, Michihiro Yasunaga, et al.2024 · 79 citations
13. A Comprehensive Survey on Long Context Language ModelingarXiv:2503.17407Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.2025 · 64 citations
14. RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement LearningarXiv:2410.02089Jonas Gehring, Kunhao Zheng, Jade Copet, et al.2024 · 51 citations
15. Introducing v0.5 of the AI Safety Benchmark from MLCommonsarXiv:2404.12241Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.2024 · 38 citations
16. A Survey on Evaluation of LLM-based AgentsFindings of the Association for Computational LinguisticsAsaf Yehudai, Lilach Eden, Alan Li, et al.2026 · 21 citations
17. Examining False Positives under Inference Scaling for Mathematical ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Yu Wang, Nan Yang, Liang Wang, et al.2025 · 9 citations
18. Localized Cultural Knowledge is Conserved and Controllable in Large Language ModelsFindings of the Association for Computational LinguisticsVeniamin Veselovsky, Berke Argın, Benedikt Stroebl, et al.2026 · 7 citations
19. When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Ammar Khairi, Daniel D'souza, Ye Shen, et al.2025 · 6 citations
20. Lost in Simulation: LLM-Simulated Users are Unreliable Proxies for Human Users in Agentic EvaluationsAnnual Meeting of the Association for Computational Linguistics (ACL)Preethi Seshadri, Samuel Cahyawijaya, Ayomide Odumakinde, et al.2026 · 5 citations
21. 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
22. Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and OpportunitiesAnnual Meeting of the Association for Computational Linguistics (ACL)Changdae Oh, Seongheon Park, To Eun Kim, et al.2026 · 4 citations
23. Agentic CLEAR: Automating Multi-Level Evaluation of LLM AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Asaf Yehudai, Lilach Eden, Michal Shmueli-Scheuer2026
24. Efficient Agent Evaluation via Diversity-Guided User SimulationAnnual Meeting of the Association for Computational Linguistics (ACL)Itay Nakash, George Kour, Ateret Anaby Tavor2026
25. Follow the Path: Reasoning over Knowledge Graph Paths to Improve Large Language Model FactualityFindings of the Association for Computational LinguisticsMike Zhang, Johannes Bjerva, Russa Biswas2026
26. What Moves the Pareto Frontier in Tool-Using Agents? A Compute-Aware Study of ReAct VariantsAnnual Meeting of the Association for Computational Linguistics (ACL)Rishi N. Simhadri2026

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