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Who cites Owain Evans

2,558 citations of their works from 2,381 papers of our library (of the 149,439 whose bibliographies we read) · 675 with a page here, the most cited first · page 3 of 7 · 201–300 · ← Owain Evans

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  1. Context-faithful Prompting for Large Language ModelsFindings of the Association for Computational LinguisticsWenxuan Zhou, Sheng Zhang, Hoifung Poon, et al.2023 · 148 citations
  2. A Roadmap to Pluralistic AlignmentarXiv:2402.05070Taylor Sorensen, Jared Moore, Jillian Fisher, et al.2024 · 143 citations
  3. LongRoPE: Extending LLM Context Window Beyond 2 Million TokensarXiv:2402.13753Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, et al.2024 · 142 citations
  4. 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
  5. Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-CollaborationarXiv:2307.05300Zhenhailong Wang, Shaoguang Mao, Wenshan Wu, et al.2023 · 140 citations
  6. To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoningarXiv:2409.12183Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.2024 · 138 citations
  7. Investigating Data Contamination in Modern Benchmarks for Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Chunyuan Deng, Yilun Zhao, Xiangru Tang, et al.2024 · 137 citations
  8. 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
  9. 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
  10. 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
  11. Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology ViewAnnual Meeting of the Association for Computational Linguistics (ACL)Jintian Zhang, Xin Xu, Ningyu Zhang, et al.2024 · 134 citations
  12. Simple synthetic data reduces sycophancy in large language modelsarXiv:2308.03958Jerry Wei, Da Huang, Yifeng Lu, et al.2023 · 134 citations
  13. FLUTE: Figurative Language Understanding through Textual ExplanationsConference on Empirical Methods in Natural Language Processing (EMNLP)Tuhin Chakrabarty, Arkadiy Saakyan, Debanjan Ghosh, et al.2022 · 133 citations
  14. ZeroSCROLLS: A Zero-Shot Benchmark for Long Text UnderstandingFindings of the Association for Computational LinguisticsUri Shaham, Maor Ivgi, Avia Efrat, et al.2023 · 132 citations
  15. Progressive-Hint Prompting Improves Reasoning in Large Language ModelsarXiv:2304.09797Chuanyang Zheng, Zhengying Liu, Enze Xie, et al.2023 · 131 citations
  16. Deductive Verification of Chain-of-Thought ReasoningConference on Neural Information Processing Systems (NeurIPS)Zhan Ling, Yunhao Fang, Xuanlin Li, et al.2023 · 130 citations
  17. Natural Language Reasoning, A SurveyACM Computing SurveysFei Yu, Hongbo Zhang, Prayag Tiwari, et al.2023 · 130 citations
  18. 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
  19. Faithful Logical Reasoning via Symbolic Chain-of-ThoughtAnnual Meeting of the Association for Computational Linguistics (ACL)Jundong Xu, Hao Fei, Liangming Pan, et al.2024 · 129 citations
  20. Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-TuningarXiv:2303.15647Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.2023 · 129 citations
  21. Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled DataFindings of the Association for Computational LinguisticsKashun Shum, Shizhe Diao, Tong Zhang2023 · 128 citations
  22. Scaling Sentence Embeddings with Large Language ModelsFindings of the Association for Computational LinguisticsTing Jiang, Shaohan Huang, Zhongzhi Luan, et al.2024 · 127 citations
  23. The WMDP Benchmark: Measuring and Reducing Malicious Use With UnlearningarXiv:2403.03218Nathaniel Li, Alexander Pan, Anjali Gopal, et al.2024 · 127 citations
  24. 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
  25. Can Language Models Solve Graph Problems in Natural Language?Conference on Neural Information Processing Systems (NeurIPS)Heng Wang, Shangbin Feng, Tianxing He, et al.2023 · 124 citations
  26. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 124 citations
  27. 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
  28. Large Language Models as Tool MakersarXiv:2305.17126Tianle Cai, Xuezhi Wang, Tengyu Ma, et al.2023 · 123 citations
  29. Pretraining Language Models with Human PreferencesarXiv:2302.08582Tomasz Korbak, Kejian Shi, Angelica Chen, et al.2023 · 121 citations
  30. UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Ahmed Masry, Parsa Kavehzadeh, Xuan Long Do, et al.2023 · 121 citations
  31. 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
  32. Alignment of Language AgentsarXiv:2103.14659Zachary Kenton, Tom Everitt, Laura Weidinger, et al.2021 · 120 citations
  33. Best Practices and Lessons Learned on Synthetic DataarXiv:2404.07503Ruibo Liu, Jerry Wei, Fangyu Liu, et al.2024 · 119 citations
  34. Measuring Progress on Scalable Oversight for Large Language ModelsarXiv:2211.03540Samuel R. Bowman, Jeeyoon Hyun, Ethan Perez, et al.2022 · 117 citations
  35. Large Language Models Understand and Can be Enhanced by Emotional StimuliarXiv:2307.11760Cheng Li, Jindong Wang, Yixuan Zhang, et al.2023 · 116 citations
  36. LMMs-Eval: Reality Check on the Evaluation of Large Multimodal ModelsFindings of the Association for Computational LinguisticsKaichen Zhang, Bo Li, Peiyuan Zhang, et al.2025 · 115 citations
  37. Fundamental Limitations of Alignment in Large Language ModelsarXiv:2304.11082Yotam Wolf, Noam Wies, Oshri Avnery, et al.2023 · 114 citations
  38. Ground-Truth Labels Matter: A Deeper Look into Input-Label DemonstrationsConference on Empirical Methods in Natural Language Processing (EMNLP)Kang Min Yoo, Junyeob Kim, Hyuhng Joon Kim, et al.2022 · 114 citations
  39. ALLaM: Large Language Models for Arabic and EnglisharXiv:2407.15390M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.2024 · 113 citations
  40. 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
  41. Don't Make Your LLM an Evaluation Benchmark CheaterarXiv:2311.01964Kun Zhou, Yutao Zhu, Zhipeng Chen, et al.2023 · 112 citations
  42. RLHF Workflow: From Reward Modeling to Online RLHFarXiv:2405.07863Hanze Dong, Wei Xiong, Bo Pang, et al.2024 · 111 citations
  43. Better Zero-Shot Reasoning with Role-Play PromptingarXiv:2308.07702Aobo Kong, Shiwan Zhao, Hao Chen, et al.2023 · 110 citations
  44. Can Machines Learn Morality? The Delphi ExperimentarXiv:2110.07574Liwei Jiang, Jena D. Hwang, Chandra Bhagavatula, et al.2021 · 110 citations
  45. Evaluating the Performance of Large Language Models on GAOKAO BenchmarkarXiv:2305.12474Xiaotian Zhang, Chunyang Li, Yi Zong, et al.2023 · 109 citations
  46. Red-Teaming Large Language Models using Chain of Utterances for Safety-AlignmentarXiv:2308.09662Rishabh Bhardwaj, Soujanya Poria2023 · 108 citations
  47. Multi-Step Reasoning with Large Language Models, a SurveyACM Computing SurveysAske Plaat, Annie Wong, Suzan Verberne, et al.2024 · 106 citations
  48. A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and RecommendationsConference on Empirical Methods in Natural Language Processing (EMNLP)Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.2024 · 105 citations
  49. WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the WildarXiv:2406.04770Bill Yuchen Lin, Yuntian Deng, Khyathi Chandu, et al.2024 · 105 citations
  50. 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
  51. Studying Large Language Model Generalization with Influence FunctionsarXiv:2308.03296Roger Grosse, Juhan Bae, Cem Anil, et al.2023 · 105 citations
  52. Chain of Agents: Large Language Models Collaborating on Long-Context TasksConference on Neural Information Processing Systems (NeurIPS)Yusen Zhang, Ruoxi Sun, Yanfei Chen, et al.2024 · 104 citations
  53. Model evaluation for extreme risksarXiv:2305.15324Toby Shevlane, Sebastian Farquhar, Ben Garfinkel, et al.2023 · 104 citations
  54. MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 103 citations
  55. Can we trust the evaluation on ChatGPT?Workshop on Trustworthy NLPRachith Aiyappa, Jisun An, Haewoon Kwak, et al.2023 · 103 citations
  56. Shadow Alignment: The Ease of Subverting Safely-Aligned Language ModelsarXiv:2310.02949Xianjun Yang, Xiao Wang, Qi Zhang, et al.2023 · 103 citations
  57. PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt OptimizationarXiv:2310.16427Xinyuan Wang, Chenxi Li, Zhen Wang, et al.2023 · 102 citations
  58. Debating with More Persuasive LLMs Leads to More Truthful AnswersarXiv:2402.06782Akbir Khan, John Hughes, Dan Valentine, et al.2024 · 101 citations
  59. FactPEGASUS: Factuality-Aware Pre-training and Fine-tuning for Abstractive SummarizationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)David Wan, Mohit Bansal2022 · 101 citations
  60. FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsarXiv:2307.10928Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.2023 · 100 citations
  61. 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
  62. 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
  63. FELM: Benchmarking Factuality Evaluation of Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Shiqi Chen, Yiran Zhao, Jinghan Zhang, et al.2023 · 99 citations
  64. Chain of Draft: Thinking Faster by Writing LessarXiv:2502.18600Silei Xu, Wenhao Xie, Lingxiao Zhao, et al.2025 · 98 citations
  65. Hybrid LLM: Cost-Efficient and Quality-Aware Query RoutingarXiv:2404.14618Dujian Ding, Ankur Mallick, Chi Wang, et al.2024 · 98 citations
  66. LongAlign: A Recipe for Long Context Alignment of Large Language ModelsarXiv:2401.18058Yushi Bai, Xin Lv, Jiajie Zhang, et al.2024 · 98 citations
  67. MAmmoTH2: Scaling Instructions from the WebConference on Neural Information Processing Systems (NeurIPS)Xiang Yue, Tuney Zheng, Ge Zhang, et al.2024 · 96 citations
  68. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 96 citations
  69. The Platonic Representation HypothesisarXiv:2405.07987Minyoung Huh, Brian Cheung, Tongzhou Wang, et al.2024 · 96 citations
  70. INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language ModelsarXiv:2306.04757Yew Ken Chia, Pengfei Hong, Lidong Bing, et al.2023 · 96 citations
  71. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
  72. NLPositionality: Characterizing Design Biases of Datasets and ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Sebastin Santy, Jenny Liang, Ronan Le Bras, et al.2023 · 95 citations
  73. 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
  74. Training Socially Aligned Language Models on Simulated Social InteractionsarXiv:2305.16960Ruibo Liu, Ruixin Yang, Chenyan Jia, et al.2023 · 94 citations
  75. Do-Not-Answer: Evaluating Safeguards in LLMsFindings of the Association for Computational LinguisticsYuxia Wang, Haonan Li, Xudong Han, et al.2024 · 93 citations
  76. LLMs Are Few-Shot In-Context Low-Resource Language LearnersConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Samuel Cahyawijaya, Holy Lovenia, Pascale Fung2024 · 93 citations
  77. 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
  78. A Survey of Reinforcement Learning from Human FeedbackTransactions on Machine Learning ResearchTimo Kaufmann, Paul Weng, Viktor Bengs, et al.2023 · 92 citations
  79. 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
  80. Proving Test Set Contamination in Black Box Language ModelsarXiv:2310.17623Yonatan Oren, Nicole Meister, Niladri Chatterji, et al.2023 · 92 citations
  81. Universal Self-Consistency for Large Language Model GenerationarXiv:2311.17311Xinyun Chen, Renat Aksitov, Uri Alon, et al.2023 · 92 citations
  82. PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM InferenceFindings of the Association for Computational LinguisticsDongjie Yang, Xiaodong Han, Yan Gao, et al.2024 · 91 citations
  83. “My Answer is C”: First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language ModelsFindings of the Association for Computational LinguisticsXinpeng Wang, Bolei Ma, Chengzhi Hu, et al.2024 · 91 citations
  84. SciEval: A Multi-Level Large Language Model Evaluation Benchmark for Scientific ResearchProceedings of the AAAI Conference on Artificial IntelligenceLiangtai Sun, Yang Han, Zihan Zhao, et al.2023 · 91 citations
  85. Rephrasing the Web: A Recipe for Compute and Data-Efficient Language ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Pratyush Maini, Skyler Seto, Richard Bai, et al.2024 · 90 citations
  86. Alignment for HonestyConference on Neural Information Processing Systems (NeurIPS)Yuqing Yang, Ethan Chern, Xipeng Qiu, et al.2023 · 90 citations
  87. 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
  88. SuperGPQA: Scaling LLM Evaluation across 285 Graduate DisciplinesarXiv:2502.14739M-A-P Team, Xinrun Du, Yifan Yao, et al.2025 · 89 citations
  89. Task Contamination: Language Models May Not Be Few-Shot AnymoreProceedings of the AAAI Conference on Artificial IntelligenceChangmao Li, Jeffrey Flanigan2023 · 89 citations
  90. Small Language Models: Survey, Measurements, and InsightsarXiv:2409.15790Zhenyan Lu, Xiang Li, Dongqi Cai, et al.2024 · 88 citations
  91. Large Language Models as General Pattern MachinesarXiv:2307.04721Suvir Mirchandani, Fei Xia, Pete Florence, et al.2023 · 88 citations
  92. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
  93. A Survey of Large Language Models in Medicine: Progress, Application, and ChallengearXiv:2311.05112Hongjian Zhou, Fenglin Liu, Boyang Gu, et al.2023 · 87 citations
  94. NL-Augmenter: A Framework for Task-Sensitive Natural Language AugmentationNorthern European Journal of Language TechnologyKaustubh Dhole, Varun Gangal, Sebastian Gehrmann, et al.2023 · 86 citations
  95. The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMsConference on Neural Information Processing Systems (NeurIPS)Laura Ruis, Akbir Khan, Stella Biderman, et al.2022 · 86 citations
  96. LLMs cannot find reasoning errors, but can correct them given the error locationFindings of the Association for Computational LinguisticsGladys Tyen, Hassan Mansoor, Victor Carbune, et al.2024 · 85 citations
  97. SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural ReasoningConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Bin Wang, Zhengyuan Liu, Xin Huang, et al.2024 · 85 citations
  98. DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question AnsweringAnnual Meeting of the Association for Computational Linguistics (ACL)Ella Neeman, Roee Aharoni, Or Honovich, et al.2023 · 85 citations
  99. Improving Alignment and Robustness with Circuit BreakersConference on Neural Information Processing Systems (NeurIPS)Andy Zou, Long Phan, Justin Wang, et al.2024 · 83 citations
  100. ORCA: A Challenging Benchmark for Arabic Language UnderstandingFindings of the Association for Computational LinguisticsAbdelRahim Elmadany, ElMoatez Billah Nagoudi, Muhammad Abdul-Mageed2023 · 83 citations

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