Who cites Kejian Shi
- PaLM 2 Technical ReportarXiv:2305.10403Rohan Anil, Andrew M. Dai, Orhan Firat, et al.2023 · 977 citations
- Universal and Transferable Adversarial Attacks on Aligned Language ModelsarXiv:2307.15043Andy Zou, Zifan Wang, Nicholas Carlini, et al.2023 · 951 citations
- Self-RAG: Learning to Retrieve, Generate, and Critique through Self-ReflectionarXiv:2310.11511Akari Asai, Zeqiu Wu, Yizhong Wang, et al.2023 · 662 citations
- Jailbroken: How Does LLM Safety Training Fail?Conference on Neural Information Processing Systems (NeurIPS)Alexander Wei, Nika Haghtalab, Jacob Steinhardt2023 · 659 citations
- Jailbreaking Black Box Large Language Models in Twenty QueriesarXiv:2310.08419Patrick Chao, Alexander Robey, Edgar Dobriban, et al.2023 · 533 citations
- AlpacaFarm: A Simulation Framework for Methods that Learn from Human FeedbackConference on Neural Information Processing Systems (NeurIPS)Yann Dubois, Xuechen Li, Rohan Taori, et al.2023 · 424 citations
- Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 300 citations
- XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language ModelsarXiv:2308.01263Paul Rottger, Hannah Rose Kirk, Bertie Vidgen, et al.2023 · 227 citations
- Baseline Defenses for Adversarial Attacks Against Aligned Language ModelsarXiv:2309.00614Neel Jain, Avi Schwarzschild, Yuxin Wen, et al.2023 · 225 citations
- Fine-Grained Human Feedback Gives Better Rewards for Language Model TrainingarXiv:2306.01693Zeqiu Wu, Yushi Hu, Weijia Shi, et al.2023 · 212 citations
- Catastrophic Jailbreak of Open-source LLMs via Exploiting GenerationarXiv:2310.06987Yangsibo Huang, Samyak Gupta, Mengzhou Xia, et al.2023 · 162 citations
- GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via CipherarXiv:2308.06463Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.2023 · 158 citations
- Jailbreak and Guard Aligned Language Models with Only Few In-Context DemonstrationsarXiv:2310.06387Zeming Wei, Yifei Wang, Ang Li, et al.2023 · 125 citations
- V-STaR: Training Verifiers for Self-Taught ReasonersarXiv:2402.06457Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.2024 · 111 citations
- Certifying LLM Safety against Adversarial PromptingarXiv:2309.02705Aounon Kumar, Chirag Agarwal, Suraj Srinivas, et al.2023 · 110 citations
- 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 · 107 citations
- Inverse Scaling: When Bigger Isn't BetterarXiv:2306.09479 · Transactions on Machine Learning Research (TMLR), 10/2023, https://openreview.net/forum?id=DwgRm72GQFIan R. McKenzie, Alexander Lyzhov, Michael Pieler, et al.2023 · 99 citations
- FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsarXiv:2307.10928Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.2023 · 94 citations
- The Language Barrier: Dissecting Safety Challenges of LLMs in Multilingual ContextsFindings of the Association for Computational LinguisticsLingfeng Shen, Weiting Tan, Sihao Chen, et al.2024 · 86 citations
- Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language GenerationTransactions of the Association for Computational Linguistics (TACL)Patrick Fernandes, Aman Madaan, Emmy Liu, et al.2023 · 84 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
- Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use CasesarXiv:2303.14742Yunjie Ji, Yong Deng, Yan Gong, et al.2023 · 62 citations
- InstructSum: A Benchmark to Evaluate Instruction-Following Capability of Large Language Models in SummarizationLanguage Resources and Evaluation Conference (LREC)Kosuke Nishida, Kyosuke Nishida, Itsumi Saito2026
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