--- title: "Who cites Kejian Shi — 150 papers of our library" description: "150 papers of the Elamur Research library cite the works of Kejian Shi, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/kejian-shi/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/kejian-shi/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Kejian Shi](https://md.research.elamur.ai/free/en/authors/kejian-shi/) / cited by # Who cites Kejian Shi 150 citations of their works from 150 papers of our library (of the 141,840 whose bibliographies we read) · 24 with a page here, the most cited first · [← Kejian Shi](https://md.research.elamur.ai/free/en/authors/kejian-shi/) 1. [**PaLM 2 Technical Report arXiv:2305.10403**Rohan Anil, Andrew M. Dai, Orhan Firat, et al.*2023 · 977 citations*](https://md.research.elamur.ai/free/en/papers/anil-2023-palm-2-technical-report/) 2. [**Universal and Transferable Adversarial Attacks on Aligned Language Models arXiv:2307.15043**Andy Zou, Zifan Wang, Nicholas Carlini, et al.*2023 · 951 citations*](https://md.research.elamur.ai/free/en/papers/zou-2023-universal-transferable-adversarial-attacks-aligned/) 3. [**Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection arXiv:2310.11511**Akari Asai, Zeqiu Wu, Yizhong Wang, et al.*2023 · 662 citations*](https://md.research.elamur.ai/free/en/papers/asai-2023-self-rag-learning-retrieve-generate/) 4. **[Jailbroken: How Does LLM Safety Training Fail?](https://md.research.elamur.ai/free/en/papers/wei-2023-jailbroken-llm-safety-training-fail/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alexander Wei, Nika Haghtalab, Jacob Steinhardt*2023 · 659 citations* 5. [**Jailbreaking Black Box Large Language Models in Twenty Queries arXiv:2310.08419**Patrick Chao, Alexander Robey, Edgar Dobriban, et al.*2023 · 533 citations*](https://md.research.elamur.ai/free/en/papers/chao-2023-jailbreaking-black-box-large-language/) 6. **[AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback](https://md.research.elamur.ai/free/en/papers/dubois-2023-alpacafarm-simulation-framework-methods-that/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yann Dubois, Xuechen Li, Rohan Taori, et al.*2023 · 424 citations* 7. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/) 8. [**XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models arXiv:2308.01263**Paul Rottger, Hannah Rose Kirk, Bertie Vidgen, et al.*2023 · 227 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2023-xstest-test-suite-identifying-exaggerated/) 9. [**Baseline Defenses for Adversarial Attacks Against Aligned Language Models arXiv:2309.00614**Neel Jain, Avi Schwarzschild, Yuxin Wen, et al.*2023 · 225 citations*](https://md.research.elamur.ai/free/en/papers/jain-2023-baseline-defenses-adversarial-attacks-against/) 10. [**Fine-Grained Human Feedback Gives Better Rewards for Language Model Training arXiv:2306.01693**Zeqiu Wu, Yushi Hu, Weijia Shi, et al.*2023 · 212 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-fine-grained-human-feedback-gives/) 11. [**Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation arXiv:2310.06987**Yangsibo Huang, Samyak Gupta, Mengzhou Xia, et al.*2023 · 162 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-catastrophic-jailbreak-open-source-llms/) 12. [**GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher arXiv:2308.06463**Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-gpt-4-too-smart-safe/) 13. [**Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations arXiv:2310.06387**Zeming Wei, Yifei Wang, Ang Li, et al.*2023 · 125 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-jailbreak-guard-aligned-language-models/) 14. [**V-STaR: Training Verifiers for Self-Taught Reasoners arXiv:2402.06457**Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/hosseini-2024-v-star-training-verifiers-self/) 15. [**Certifying LLM Safety against Adversarial Prompting arXiv:2309.02705**Aounon Kumar, Chirag Agarwal, Suraj Srinivas, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2023-certifying-llm-safety-against-adversarial/) 16. **[Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM](https://md.research.elamur.ai/free/en/papers/cao-2024-defending-against-alignment-breaking-attacks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bochuan Cao, Yuanpu Cao, Lu Lin, et al.*2024 · 107 citations* 17. [**Inverse Scaling: When Bigger Isn't Better arXiv:2306.09479 · Transactions on Machine Learning Research (TMLR), 10/2023, https://openreview.net/forum?id=DwgRm72GQF**Ian R. McKenzie, Alexander Lyzhov, Michael Pieler, et al.*2023 · 99 citations*](https://md.research.elamur.ai/free/en/papers/mckenzie-2023-inverse-scaling-bigger-isn-t/) 18. [**FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets arXiv:2307.10928**Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.*2023 · 94 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-flask-fine-grained-language-model/) 19. **[The Language Barrier: Dissecting Safety Challenges of LLMs in Multilingual Contexts](https://md.research.elamur.ai/free/en/papers/shen-2024-language-barrier-dissecting-safety-challenges/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lingfeng Shen, Weiting Tan, Sihao Chen, et al.*2024 · 86 citations* 20. **[Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Patrick Fernandes, Aman Madaan, Emmy Liu, et al.*2023 · 84 citations* 21. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/) 22. [**Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use Cases arXiv:2303.14742**Yunjie Ji, Yong Deng, Yan Gong, et al.*2023 · 62 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-exploring-impact-instruction-data/) 23. **[Bridging Cognition and Affect: Emotion-Aware Opinion Summarization using LLMs](https://md.research.elamur.ai/free/en/papers/attri-2026-bridging-cognition-affect-emotion-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Arnav Attri, Anuj Attri*2026* 24. **[InstructSum: A Benchmark to Evaluate Instruction-Following Capability of Large Language Models in Summarization](https://md.research.elamur.ai/free/en/papers/nishida-2026-instructsum-benchmark-evaluate-instruction-following/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kosuke Nishida, Kyosuke Nishida, Itsumi Saito*2026* 126 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/kejian-shi/) — Kejian Shi