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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) · 857 with a page here, the most cited first · page 3 of 9 · 201–300 · ← Nova DasSarma

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  1. OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF FrameworkarXiv:2405.11143Jian Hu, Xibin Wu, Wei Shen, et al.2024 · 140 citations
  2. Self-Alignment with Instruction BacktranslationarXiv:2308.06259Xian Li, Ping Yu, Chunting Zhou, et al.2023 · 139 citations
  3. SOTOPIA: Interactive Evaluation for Social Intelligence in Language AgentsarXiv:2310.11667Xuhui Zhou, Hao Zhu, Leena Mathur, et al.2023 · 138 citations
  4. 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
  5. 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
  6. Secrets of RLHF in Large Language Models Part I: PPOarXiv:2307.04964Rui Zheng, Shihan Dou, Songyang Gao, et al.2023 · 135 citations
  7. 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
  8. Simple synthetic data reduces sycophancy in large language modelsarXiv:2308.03958Jerry Wei, Da Huang, Yifeng Lu, et al.2023 · 134 citations
  9. The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Hannah Rose Kirk, Alexander Whitefield, Paul Rottger, et al.2024 · 133 citations
  10. 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
  11. 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
  12. Progressive-Hint Prompting Improves Reasoning in Large Language ModelsarXiv:2304.09797Chuanyang Zheng, Zhengying Liu, Enze Xie, et al.2023 · 131 citations
  13. 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
  14. Evaluating the Moral Beliefs Encoded in LLMsConference on Neural Information Processing Systems (NeurIPS)Nino Scherrer, Claudia Shi, Amir Feder, et al.2023 · 129 citations
  15. ExpertPrompting: Instructing Large Language Models to be Distinguished ExpertsarXiv:2305.14688Benfeng Xu, An Yang, Junyang Lin, et al.2023 · 128 citations
  16. 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
  17. 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
  18. Fine-tuning Language Models for FactualityarXiv:2311.08401Katherine Tian, Eric Mitchell, Huaxiu Yao, et al.2023 · 127 citations
  19. Function Vectors in Large Language ModelsarXiv:2310.15213Eric Todd, Millicent L. Li, Arnab Sen Sharma, et al.2023 · 127 citations
  20. Negative Preference Optimization: From Catastrophic Collapse to Effective UnlearningarXiv:2404.05868Ruiqi Zhang, Licong Lin, Yu Bai, et al.2024 · 126 citations
  21. Chain of Hindsight Aligns Language Models with FeedbackarXiv:2302.02676Hao Liu, Carmelo Sferrazza, Pieter Abbeel2023 · 126 citations
  22. LEVER: Learning to Verify Language-to-Code Generation with ExecutionarXiv:2302.08468Ansong Ni, Srini Iyer, Dragomir Radev, et al.2023 · 126 citations
  23. LM vs LM: Detecting Factual Errors via Cross ExaminationConference on Empirical Methods in Natural Language Processing (EMNLP)Roi Cohen, May Hamri, Mor Geva, et al.2023 · 126 citations
  24. Generative Judge for Evaluating AlignmentarXiv:2310.05470Junlong Li, Shichao Sun, Weizhe Yuan, et al.2023 · 125 citations
  25. Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and FuturearXiv:2309.15402Zheng Chu, Jingchang Chen, Qianglong Chen, et al.2023 · 125 citations
  26. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 124 citations
  27. Sleeper Agents: Training Deceptive LLMs that Persist Through Safety TrainingarXiv:2401.05566Evan Hubinger, Carson Denison, Jesse Mu, et al.2024 · 123 citations
  28. Emergent and Predictable Memorization in Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Stella Biderman, USVSN Sai Prashanth, Lintang Sutawika, et al.2023 · 123 citations
  29. Finding Neurons in a Haystack: Case Studies with Sparse ProbingarXiv:2305.01610Wes Gurnee, Neel Nanda, Matthew Pauly, et al.2023 · 123 citations
  30. Faithful Reasoning Using Large Language ModelsarXiv:2208.14271Antonia Creswell, Murray Shanahan2022 · 122 citations
  31. Pretraining Language Models with Human PreferencesarXiv:2302.08582Tomasz Korbak, Kejian Shi, Angelica Chen, et al.2023 · 121 citations
  32. The Alignment Problem from a Deep Learning PerspectivearXiv:2209.00626Richard Ngo, Lawrence Chan, Soren Mindermann2022 · 121 citations
  33. Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language ModelsarXiv:2501.09686Fengli Xu, Qianyue Hao, Zefang Zong, et al.2025 · 120 citations
  34. #InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language ModelsarXiv:2308.07074Keming Lu, Hongyi Yuan, Zheng Yuan, et al.2023 · 120 citations
  35. Best Practices and Lessons Learned on Synthetic DataarXiv:2404.07503Ruibo Liu, Jerry Wei, Fangyu Liu, et al.2024 · 119 citations
  36. 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
  37. Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive AttacksarXiv:2404.02151Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion2024 · 118 citations
  38. Measuring Progress on Scalable Oversight for Large Language ModelsarXiv:2211.03540Samuel R. Bowman, Jeeyoon Hyun, Ethan Perez, et al.2022 · 117 citations
  39. ProcessBench: Identifying Process Errors in Mathematical ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Chujie Zheng, Zhenru Zhang, Beichen Zhang, et al.2025 · 116 citations
  40. Deliberative Alignment: Reasoning Enables Safer Language ModelsarXiv:2412.16339Melody Y. Guan, Manas Joglekar, Eric Wallace, et al.2024 · 115 citations
  41. From Persona to Personalization: A Survey on Role-Playing Language AgentsarXiv:2404.18231Jiangjie Chen, Xintao Wang, Rui Xu, et al.2024 · 115 citations
  42. Fundamental Limitations of Alignment in Large Language ModelsarXiv:2304.11082Yotam Wolf, Noam Wies, Oshri Avnery, et al.2023 · 114 citations
  43. In-context Autoencoder for Context Compression in a Large Language ModelarXiv:2307.06945Tao Ge, Jing Hu, Lei Wang, et al.2023 · 114 citations
  44. ExpertQA: Expert-Curated Questions and Attributed AnswersConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Chaitanya Malaviya, Subin Lee, Sihao Chen, et al.2024 · 113 citations
  45. Skywork-Reward: Bag of Tricks for Reward Modeling in LLMsarXiv:2410.18451Chris Yuhao Liu, Liang Zeng, Jiacai Liu, et al.2024 · 112 citations
  46. ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language ModelsarXiv:2404.07738Jinheon Baek, Sujay Kumar Jauhar, Silviu Cucerzan, et al.2024 · 111 citations
  47. RLHF Workflow: From Reward Modeling to Online RLHFarXiv:2405.07863Hanze Dong, Wei Xiong, Bo Pang, et al.2024 · 111 citations
  48. INSIDE: LLMs' Internal States Retain the Power of Hallucination DetectionarXiv:2402.03744Chao Chen, Kai Liu, Ze Chen, et al.2024 · 108 citations
  49. Mechanistic Interpretability for AI Safety — A ReviewarXiv:2404.14082Leonard Bereska, Efstratios Gavves2024 · 108 citations
  50. Can LLM-Generated Misinformation Be Detected?arXiv:2309.13788Canyu Chen, Kai Shu2023 · 108 citations
  51. Red-Teaming Large Language Models using Chain of Utterances for Safety-AlignmentarXiv:2308.09662Rishabh Bhardwaj, Soujanya Poria2023 · 108 citations
  52. Nemotron-4 340B Technical ReportarXiv:2406.11704Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.2024 · 107 citations
  53. R-Judge: Benchmarking Safety Risk Awareness for LLM AgentsFindings of the Association for Computational LinguisticsTongxin Yuan, Zhiwei He, Lingzhong Dong, et al.2024 · 106 citations
  54. Disentangling Length from Quality in Direct Preference OptimizationFindings of the Association for Computational LinguisticsRyan Park, Rafael Rafailov, Stefano Ermon, et al.2024 · 105 citations
  55. 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 · 105 citations
  56. Statistical Rejection Sampling Improves Preference OptimizationarXiv:2309.06657Tianqi Liu, Yao Zhao, Rishabh Joshi, et al.2023 · 105 citations
  57. Studying Large Language Model Generalization with Influence FunctionsarXiv:2308.03296Roger Grosse, Juhan Bae, Cem Anil, et al.2023 · 105 citations
  58. REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage NormalizationarXiv:2501.03262Jian Hu, Jason Klein Liu, Haotian Xu, et al.2025 · 104 citations
  59. Model evaluation for extreme risksarXiv:2305.15324Toby Shevlane, Sebastian Farquhar, Ben Garfinkel, et al.2023 · 104 citations
  60. Towards Measuring and Modeling “Culture” in LLMs: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Muhammad Farid Adilazuarda, Sagnik Mukherjee, Pradhyumna Lavania, et al.2024 · 102 citations
  61. Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter MergingarXiv:2310.11564Joel Jang, Seungone Kim, Bill Yuchen Lin, et al.2023 · 102 citations
  62. What In-Context Learning “Learns” In-Context: Disentangling Task Recognition and Task LearningFindings of the Association for Computational LinguisticsJane Pan, Tianyu Gao, Howard Chen, et al.2023 · 102 citations
  63. The Entropy Mechanism of Reinforcement Learning for Reasoning Language ModelsarXiv:2505.22617Ganqu Cui, Yuchen Zhang, Jiacheng Chen, et al.2025 · 101 citations
  64. Debating with More Persuasive LLMs Leads to More Truthful AnswersarXiv:2402.06782Akbir Khan, John Hughes, Dan Valentine, et al.2024 · 101 citations
  65. JudgeBench: A Benchmark for Evaluating LLM-based JudgesarXiv:2410.12784Sijun Tan, Siyuan Zhuang, Kyle Montgomery, et al.2024 · 101 citations
  66. CoAnnotating: Uncertainty-Guided Work Allocation between Human and Large Language Models for Data AnnotationConference on Empirical Methods in Natural Language Processing (EMNLP)Minzhi Li, Taiwei Shi, Caleb Ziems, et al.2023 · 101 citations
  67. Personal LLM Agents: Insights and Survey about the Capability, Efficiency and SecurityarXiv:2401.05459Yuanchun Li, Hao Wen, Weijun Wang, et al.2024 · 100 citations
  68. FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsarXiv:2307.10928Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.2023 · 100 citations
  69. Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-ConstraintarXiv:2312.11456Wei Xiong, Hanze Dong, Chenlu Ye, et al.2023 · 100 citations
  70. R-Tuning: Instructing Large Language Models to Say ‘I Don't Know'Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Hanning Zhang, Shizhe Diao, Yong Lin, et al.2024 · 99 citations
  71. Unsupervised Real-Time Hallucination Detection based on the Internal States of Large Language ModelsFindings of the Association for Computational LinguisticsWeihang Su, Changyue Wang, Qingyao Ai, et al.2024 · 99 citations
  72. A Long Way to Go: Investigating Length Correlations in RLHFarXiv:2310.03716Prasann Singhal, Tanya Goyal, Jiacheng Xu, et al.2023 · 99 citations
  73. Answering Questions by Meta-Reasoning over Multiple Chains of ThoughtConference on Empirical Methods in Natural Language Processing (EMNLP)Ori Yoran, Tomer Wolfson, Ben Bogin, et al.2023 · 99 citations
  74. Make Your LLM Fully Utilize the ContextConference on Neural Information Processing Systems (NeurIPS)Shengnan An, Zexiong Ma, Zeqi Lin, et al.2024 · 97 citations
  75. Safety Alignment Should Be Made More Than Just a Few Tokens DeeparXiv:2406.05946Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, et al.2024 · 97 citations
  76. A Survey of Confidence Estimation and Calibration in Large Language ModelsarXiv:2311.08298Jiahui Geng, Fengyu Cai, Yuxia Wang, et al.2023 · 97 citations
  77. Towards Best Practices of Activation Patching in Language Models: Metrics and MethodsarXiv:2309.16042Fred Zhang, Neel Nanda2023 · 97 citations
  78. Fact-Checking the Output of Large Language Models via Token-Level Uncertainty QuantificationFindings of the Association for Computational LinguisticsEkaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, et al.2024 · 96 citations
  79. Not All Countries Celebrate Thanksgiving: On the Cultural Dominance in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Wenxuan Wang, Wenxiang Jiao, Jingyuan Huang, et al.2024 · 96 citations
  80. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 96 citations
  81. Identifying the Risks of LM Agents with an LM-Emulated SandboxarXiv:2309.15817Yangjun Ruan, Honghua Dong, Andrew Wang, et al.2023 · 96 citations
  82. INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language ModelsarXiv:2306.04757Yew Ken Chia, Pengfei Hong, Lidong Bing, et al.2023 · 96 citations
  83. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
  84. Advancing LLM Reasoning Generalists with Preference TreesarXiv:2404.02078Lifan Yuan, Ganqu Cui, Hanbin Wang, et al.2024 · 94 citations
  85. Boosting Language Models Reasoning with Chain-of-Knowledge PromptingAnnual Meeting of the Association for Computational Linguistics (ACL)Jianing Wang, Qiushi Sun, Xiang Li, et al.2024 · 94 citations
  86. Moral Foundations of Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Marwa Abdulhai, Gregory Serapio-García, Clement Crepy, et al.2024 · 94 citations
  87. Retrieval Head Mechanistically Explains Long-Context FactualityarXiv:2404.15574Wenhao Wu, Yizhong Wang, Guangxuan Xiao, et al.2024 · 94 citations
  88. Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data LakesProceedings of the VLDB EndowmentSimran Arora, Brandon Yang, Sabri Eyuboglu, et al.2023 · 94 citations
  89. Training Socially Aligned Language Models on Simulated Social InteractionsarXiv:2305.16960Ruibo Liu, Ruixin Yang, Chenyan Jia, et al.2023 · 94 citations
  90. Do-Not-Answer: Evaluating Safeguards in LLMsFindings of the Association for Computational LinguisticsYuxia Wang, Haonan Li, Xudong Han, et al.2024 · 93 citations
  91. 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
  92. A Survey of Reinforcement Learning from Human FeedbackTransactions on Machine Learning ResearchTimo Kaufmann, Paul Weng, Viktor Bengs, et al.2023 · 92 citations
  93. Do Language Models Know When They're Hallucinating References?Findings of the Association for Computational LinguisticsAyush Agrawal; Mirac Suzgun; Lester Mackey;, Adam Tauman Kalai2023 · 92 citations
  94. Proving Test Set Contamination in Black Box Language ModelsarXiv:2310.17623Yonatan Oren, Nicole Meister, Niladri Chatterji, et al.2023 · 92 citations
  95. Skywork: A More Open Bilingual Foundation ModelarXiv:2310.19341Tianwen Wei, Liang Zhao, Lichang Zhang, et al.2023 · 91 citations
  96. Scaling Laws and Interpretability of Learning from Repeated DataarXiv:2205.10487Danny Hernandez, Tom Brown, Tom Conerly, et al.2022 · 91 citations
  97. Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the ArtTransactions of the Association for Computational Linguistics (TACL)Chen Cecilia Liu, Iryna Gurevych, Anna Korhonen2025 · 90 citations
  98. Better & Faster Large Language Models via Multi-token PredictionarXiv:2404.19737Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Roziere, et al.2024 · 90 citations
  99. Alignment for HonestyConference on Neural Information Processing Systems (NeurIPS)Yuqing Yang, Ethan Chern, Xipeng Qiu, et al.2023 · 90 citations
  100. Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable SurveyConference of the European Chapter of the Association for Computational Linguistics (EACL)Sachin Kumar, Vidhisha Balachandran, Lucille Njoo, et al.2023 · 90 citations

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