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Who cites Nova DasSarma

3,936 citations of their works from 3,065 papers of our library (of the 149,439 whose bibliographies we read) · 714 with a page here, the most cited first · page 2 of 8 · 101–200 · ← Nova DasSarma

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  1. Large Language Models for Mathematical Reasoning: Progresses and ChallengesConference of the European Chapter of the Association for Computational Linguistics (EACL)Janice Ahn, Rishu Verma, Renze Lou, et al.2024 · 280 citations
  2. 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
  3. Towards Measuring the Representation of Subjective Global Opinions in Language ModelsarXiv:2306.16388Esin Durmus, Karina Nguyen, Thomas I. Liao, et al.2023 · 270 citations
  4. MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training StrategiesarXiv:2404.06395Shengding Hu, Yuge Tu, Xu Han, et al.2024 · 269 citations
  5. Measuring Faithfulness in Chain-of-Thought ReasoningarXiv:2307.13702Tamera Lanham, Anna Chen, Ansh Radhakrishnan, et al.2023 · 262 citations
  6. DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT ModelsConference on Neural Information Processing Systems (NeurIPS)Boxin Wang, Weixin Chen, Hengzhi Pei, et al.2023 · 259 citations
  7. Why Can GPT Learn In-Context? Language Models Secretly Perform Gradient Descent as Meta-OptimizersFindings of the Association for Computational LinguisticsDamai Dai, Yutao Sun, Li Dong, et al.2023 · 257 citations
  8. Humanity's Last ExamNatureLong Phan, Alice Gatti, Ziwen Han, et al.2025 · 256 citations
  9. Aya Model: An Instruction Finetuned Open-Access Multilingual Language ModelarXiv:2402.07827Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.2024 · 253 citations
  10. RAFT: Reward rAnked FineTuning for Generative Foundation Model AlignmentarXiv:2304.06767Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.2023 · 252 citations
  11. Tree of Attacks: Jailbreaking Black-Box LLMs AutomaticallyConference on Neural Information Processing Systems (NeurIPS)Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, et al.2023 · 251 citations
  12. Language Models can Solve Computer TasksConference on Neural Information Processing Systems (NeurIPS)Geunwoo Kim, Pierre Baldi, Stephen McAleer2023 · 249 citations
  13. Transformers learn in-context by gradient descentarXiv:2212.07677Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, et al.2022 · 247 citations
  14. XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language ModelsarXiv:2308.01263Paul Rottger, Hannah Rose Kirk, Bertie Vidgen, et al.2023 · 244 citations
  15. LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation DatasetarXiv:2309.11998Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.2023 · 242 citations
  16. BlenderBot 3: a deployed conversational agent that continually learns to responsibly engagearXiv:2208.03188Kurt Shuster, Jing Xu, Mojtaba Komeili, et al.2022 · 241 citations
  17. Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt InjectionarXiv:2302.12173Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, et al.2023 · 239 citations
  18. TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
  19. Baseline Defenses for Adversarial Attacks Against Aligned Language ModelsarXiv:2309.00614Neel Jain, Avi Schwarzschild, Yuxin Wen, et al.2023 · 236 citations
  20. Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human SupervisionConference on Neural Information Processing Systems (NeurIPS)Zhiqing Sun, Yikang Shen, Qinhong Zhou, et al.2023 · 236 citations
  21. What learning algorithm is in-context learning? Investigations with linear modelsarXiv:2211.15661Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al.2022 · 236 citations
  22. Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language ModelsarXiv:2405.01535Seungone Kim, Juyoung Suk, Shayne Longpre, et al.2024 · 234 citations
  23. Steering Language Models With Activation EngineeringarXiv:2308.10248Alexander Matt Turner, Lisa Thiergart, Gavin Leech, et al.2023 · 233 citations
  24. Progress measures for grokking via mechanistic interpretabilityarXiv:2301.05217Neel Nanda, Lawrence Chan, Tom Lieberum, et al.2023 · 228 citations
  25. Self-critiquing models for assisting human evaluatorsarXiv:2206.05802William Saunders, Catherine Yeh, Jeff Wu, et al.2022 · 228 citations
  26. Reinforced Self-Training (ReST) for Language ModelingarXiv:2308.08998Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, et al.2023 · 224 citations
  27. Fine-Grained Human Feedback Gives Better Rewards for Language Model TrainingarXiv:2306.01693Zeqiu Wu, Yushi Hu, Weijia Shi, et al.2023 · 223 citations
  28. Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' AlignmentarXiv:2308.05374Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li2023 · 223 citations
  29. Med-HALT: Medical Domain Hallucination Test for Large Language ModelsConference on Computational Natural Language Learning (CoNLL)Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu2023 · 221 citations
  30. AlpaGasus: Training A Better Alpaca with Fewer DataarXiv:2307.08701Lichang Chen, Shiyang Li, Jun Yan, et al.2023 · 220 citations
  31. Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language ModelsarXiv:2308.16149Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, et al.2023 · 218 citations
  32. Teaching language models to support answers with verified quotesarXiv:2203.11147Jacob Menick, Maja Trebacz, Vladimir Mikulik, et al.2022 · 218 citations
  33. Safe RLHF: Safe Reinforcement Learning from Human FeedbackarXiv:2310.12773Josef Dai, Xuehai Pan, Ruiyang Sun, et al.2023 · 217 citations
  34. Scalable Extraction of Training Data from (Production) Language ModelsarXiv:2311.17035Milad Nasr, Nicholas Carlini, Jonathan Hayase, et al.2023 · 211 citations
  35. Prompting GPT-3 To Be ReliablearXiv:2210.09150Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.2022 · 210 citations
  36. Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2arXiv:2311.10702Hamish Ivison, Yizhong Wang, Valentina Pyatkin, et al.2023 · 207 citations
  37. LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language ModelsarXiv:2305.13711Yen-Ting Lin, Yun-Nung Chen2023 · 207 citations
  38. RRHF: Rank Responses to Align Language Models with Human Feedback without tearsarXiv:2304.05302Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.2023 · 201 citations
  39. OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text DocumentsConference on Neural Information Processing Systems (NeurIPS)Hugo Laurençon, Lucile Saulnier, Leo Tronchon, et al.2023 · 197 citations
  40. Refusal in Language Models Is Mediated by a Single DirectionarXiv:2406.11717Andy Arditi, Oscar Obeso, Aaquib Syed, et al.2024 · 196 citations
  41. LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation MethodsarXiv:2412.05579Haitao Li, Qian Dong, Junjie Chen, et al.2024 · 195 citations
  42. Multilingual Jailbreak Challenges in Large Language ModelsarXiv:2310.06474Yue Deng, Wenxuan Zhang, Sinno Jialin Pan, et al.2023 · 192 citations
  43. On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Omar Shaikh, Hongxin Zhang, William Held, et al.2023 · 192 citations
  44. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesarXiv:2406.06608Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 189 citations
  45. ELEPHANT: Measuring and understanding social sycophancy in LLMsScienceMyra Cheng, Sunny Yu, Cinoo Lee, et al.2025 · 188 citations
  46. Eliciting Latent Predictions from Transformers with the Tuned LensarXiv:2303.08112Nora Belrose, Igor Ostrovsky, Lev McKinney, et al.2023 · 188 citations
  47. Preference Ranking Optimization for Human AlignmentProceedings of the AAAI Conference on Artificial IntelligenceFeifan Song, Bowen Yu, Minghao Li, et al.2023 · 188 citations
  48. Low-Resource Languages Jailbreak GPT-4arXiv:2310.02446Zheng-Xin Yong, Cristina Menghini, Stephen H. Bach2023 · 183 citations
  49. Knowledge Conflicts for LLMs: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.2024 · 182 citations
  50. Adapting Language Models to Compress ContextsConference on Empirical Methods in Natural Language Processing (EMNLP)Alexis Chevalier, Alexander Wettig, Anirudh Ajith, et al.2023 · 182 citations
  51. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 182 citations
  52. ToolQA: A Dataset for LLM Question Answering with External ToolsConference on Neural Information Processing Systems (NeurIPS)Yuchen Zhuang, Yue Yu, Kuan Wang, et al.2023 · 182 citations
  53. CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 LanguagesLanguage Resources and Evaluation Conference (LREC)Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai, et al.2023 · 181 citations
  54. Learning to Compress Prompts with Gist TokensConference on Neural Information Processing Systems (NeurIPS)Jesse Mu, Xiang Lisa Li, Noah Goodman2023 · 178 citations
  55. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
  56. Aligning Large Multimodal Models with Factually Augmented RLHFarXiv:2309.14525Zhiqing Sun, Sheng Shen, Shengcao Cao, et al.2023 · 176 citations
  57. OpenChat: Advancing Open-source Language Models with Mixed-Quality DataarXiv:2309.11235Guan Wang, Sijie Cheng, Xianyuan Zhan, et al.2023 · 174 citations
  58. AI Alignment: A Comprehensive SurveyarXiv:2310.19852Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.2023 · 173 citations
  59. Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak SupervisionarXiv:2312.09390Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.2023 · 172 citations
  60. Deduplicating Training Data Mitigates Privacy Risks in Language ModelsarXiv:2202.06539Nikhil Kandpal, Eric Wallace, Colin Raffel2022 · 172 citations
  61. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 171 citations
  62. Catastrophic Jailbreak of Open-source LLMs via Exploiting GenerationarXiv:2310.06987Yangsibo Huang, Samyak Gupta, Mengzhou Xia, et al.2023 · 169 citations
  63. GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak PromptsarXiv:2309.10253Jiahao Yu, Xingwei Lin, Zheng Yu, et al.2023 · 169 citations
  64. The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False DatasetsarXiv:2310.06824Samuel Marks, Max Tegmark2023 · 169 citations
  65. GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via CipherarXiv:2308.06463Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.2023 · 168 citations
  66. WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMsConference on Neural Information Processing Systems (NeurIPS)Seungju Han, Kavel Rao, Allyson Ettinger, et al.2024 · 165 citations
  67. Measuring short-form factuality in large language modelsarXiv:2411.04368Jason Wei, Nguyen Karina, Hyung Won Chung, et al.2024 · 160 citations
  68. Jamba: A Hybrid Transformer-Mamba Language ModelarXiv:2403.19887Opher Lieber, Barak Lenz, Hofit Bata, et al.2024 · 159 citations
  69. In-Context Learning Creates Task VectorsFindings of the Association for Computational LinguisticsRoee Hendel, Mor Geva, Amir Globerson2023 · 159 citations
  70. Leveraging Large Language Models for Multiple Choice Question AnsweringarXiv:2210.12353Joshua Robinson, Christopher Michael Rytting, David Wingate2022 · 157 citations
  71. Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-ExpertsFindings of the Association for Computational LinguisticsHaoxiang Wang, Wei Xiong, Tengyang Xie, et al.2024 · 153 citations
  72. Iterative Reasoning Preference OptimizationConference on Neural Information Processing Systems (NeurIPS)Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.2024 · 153 citations
  73. Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAsarXiv:2503.01743Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.2025 · 152 citations
  74. The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context LearningarXiv:2312.01552Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, et al.2023 · 150 citations
  75. Self-Evaluation Guided Beam Search for ReasoningConference on Neural Information Processing Systems (NeurIPS)Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.2023 · 149 citations
  76. Language Model Behavior: A Comprehensive SurveyComputational LinguisticsTyler A. Chang, Benjamin K. Bergen2024 · 148 citations
  77. Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with NothingarXiv:2406.08464Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.2024 · 148 citations
  78. MiniLLM: On-Policy Distillation of Large Language ModelsarXiv:2306.08543Yuxian Gu, Li Dong, Furu Wei, et al.2023 · 144 citations
  79. A Roadmap to Pluralistic AlignmentarXiv:2402.05070Taylor Sorensen, Jared Moore, Jillian Fisher, et al.2024 · 143 citations
  80. Understanding the Effects of RLHF on LLM Generalisation and DiversityarXiv:2310.06452Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, et al.2023 · 143 citations
  81. Many-Shot In-Context LearningConference on Neural Information Processing Systems (NeurIPS)Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.2024 · 142 citations
  82. DeepInception: Hypnotize Large Language Model to Be JailbreakerarXiv:2311.03191Xuan Li, Zhanke Zhou, Jianing Zhu, et al.2023 · 141 citations
  83. Detecting Language Model Attacks with PerplexityarXiv:2308.14132Gabriel Alon, Michael Kamfonas2023 · 141 citations
  84. SLiC-HF: Sequence Likelihood Calibration with Human FeedbackarXiv:2305.10425Yao Zhao, Rishabh Joshi, Tianqi Liu, et al.2023 · 141 citations
  85. Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction StrategiesTransactions of the Association for Computational Linguistics (TACL)Liangming Pan, Michael Saxon, Wenda Xu, et al.2024 · 140 citations
  86. OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF FrameworkarXiv:2405.11143Jian Hu, Xibin Wu, Wei Shen, et al.2024 · 140 citations
  87. Self-Alignment with Instruction BacktranslationarXiv:2308.06259Xian Li, Ping Yu, Chunting Zhou, et al.2023 · 139 citations
  88. SOTOPIA: Interactive Evaluation for Social Intelligence in Language AgentsarXiv:2310.11667Xuhui Zhou, Hao Zhu, Leena Mathur, et al.2023 · 138 citations
  89. InFoBench: Evaluating Instruction Following Ability in Large Language ModelsFindings of the Association for Computational LinguisticsYiwei Qin, Kaiqiang Song, Yebowen Hu, et al.2024 · 136 citations
  90. Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow InstructionsarXiv:2309.07875Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, et al.2023 · 135 citations
  91. Secrets of RLHF in Large Language Models Part I: PPOarXiv:2307.04964Rui Zheng, Shihan Dou, Songyang Gao, et al.2023 · 135 citations
  92. Self-Knowledge Guided Retrieval Augmentation for Large Language ModelsFindings of the Association for Computational LinguisticsYile Wang, Peng Li, Maosong Sun, et al.2023 · 135 citations
  93. Prompting is not a substitute for probability measurements in large language modelsConference on Empirical Methods in Natural Language Processing (EMNLP)Jennifer Hu, Roger Levy2023 · 133 citations
  94. Improving Language Model Negotiation with Self-Play and In-Context Learning from AI FeedbackarXiv:2305.10142Yao Fu, Hao Peng, Tushar Khot, et al.2023 · 132 citations
  95. You reap what you sow: On the Challenges of Bias Evaluation Under Multilingual SettingsBigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language ModelsZeerak Talat, Aurélie Névéol, Stella Biderman, et al.2022 · 130 citations
  96. AceGPT, Localizing Large Language Models in ArabicConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Huang Huang, Fei Yu, Jianqing Zhu, et al.2024 · 127 citations
  97. SafeDecoding: Defending against Jailbreak Attacks via Safety-Aware DecodingAnnual Meeting of the Association for Computational Linguistics (ACL)Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.2024 · 127 citations
  98. Fine-tuning Language Models for FactualityarXiv:2311.08401Katherine Tian, Eric Mitchell, Huaxiu Yao, et al.2023 · 127 citations
  99. Negative Preference Optimization: From Catastrophic Collapse to Effective UnlearningarXiv:2404.05868Ruiqi Zhang, Licong Lin, Yu Bai, et al.2024 · 126 citations
  100. LEVER: Learning to Verify Language-to-Code Generation with ExecutionarXiv:2302.08468Ansong Ni, Srini Iyer, Dragomir Radev, et al.2023 · 126 citations

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