Elamur Research⌕
☰
home / authors / Tom Conerly / cited by / page 4

Who cites Tom Conerly

2,945 citations of their works from 2,604 papers of our library (of the 149,439 whose bibliographies we read) · 729 with a page here, the most cited first · page 4 of 8 · 301–400 · ← Tom Conerly

1 2 3 4 5 … 8

  1. Reward Design with Language ModelsarXiv:2303.00001Minae Kwon, Sang Michael Xie, Kalesha Bullard, et al.2023 · 73 citations
  2. What Language Model to Train if You Have One Million GPU Hours?arXiv:2210.15424Teven Le Scao, Thomas Wang, Daniel Hesslow, et al.2022 · 73 citations
  3. A Primer on the Inner Workings of Transformer-based Language ModelsarXiv:2405.00208Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.2024 · 72 citations
  4. Black-Box Prompt Optimization: Aligning Large Language Models without Model TrainingAnnual Meeting of the Association for Computational Linguistics (ACL)Jiale Cheng, Xiao Liu, Kehan Zheng, et al.2024 · 72 citations
  5. From r to Q*: Your Language Model is Secretly a Q-FunctionarXiv:2404.12358Rafael Rafailov, Joey Hejna, Ryan Park, et al.2024 · 72 citations
  6. HelpSteer: Multi-attribute Helpfulness Dataset for SteerLMConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Zhilin Wang, Yi Dong, Jiaqi Zeng, et al.2024 · 72 citations
  7. Quantifying Uncertainty in Answers from any Language Model and Enhancing their TrustworthinessAnnual Meeting of the Association for Computational Linguistics (ACL)Jiuhai Chen, Jonas Mueller2024 · 72 citations
  8. Secrets of RLHF in Large Language Models Part II: Reward ModelingarXiv:2401.06080Binghai Wang, Rui Zheng, Lu Chen, et al.2024 · 72 citations
  9. Chain-of-Thought Hub: A Continuous Effort to Measure Large Language Models' Reasoning PerformancearXiv:2305.17306Yao Fu, Litu Ou, Mingyu Chen, et al.2023 · 72 citations
  10. Unveiling the Implicit Toxicity in Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaxin Wen, Pei Ke, Hao Sun, et al.2023 · 72 citations
  11. Factually Consistent Summarization via Reinforcement Learning with Textual Entailment FeedbackAnnual Meeting of the Association for Computational Linguistics (ACL)Paul Roit, Johan Ferret, Lior Shani, et al.2023 · 70 citations
  12. Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language ModelsarXiv:2305.14705Sheng Shen, Le Hou, Yanqi Zhou, et al.2023 · 70 citations
  13. Aligner: Efficient Alignment by Learning to CorrectConference on Neural Information Processing Systems (NeurIPS)Jiaming Ji, Boyuan Chen, Hantao Lou, et al.2024 · 69 citations
  14. Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoying Zhang, Baolin Peng, Ye Tian, et al.2024 · 69 citations
  15. Apertus: Democratizing Open and Compliant LLMs for Global Language EnvironmentsAnnual Meeting of the Association for Computational Linguistics (ACL)Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.2026 · 68 citations
  16. A Thorough Examination of Decoding Methods in the Era of LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Chufan Shi, Haoran Yang, Deng Cai, et al.2024 · 68 citations
  17. Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Haoxiang Wang, Yong Lin, Wei Xiong, et al.2024 · 68 citations
  18. LLMs Know More Than They Show: On the Intrinsic Representation of LLM HallucinationsarXiv:2410.02707Hadas Orgad, Michael Toker, Zorik Gekhman, et al.2024 · 68 citations
  19. Branch-Solve-Merge Improves Large Language Model Evaluation and GenerationarXiv:2310.15123Swarnadeep Saha, Omer Levy, Asli Celikyilmaz, et al.2023 · 68 citations
  20. OffsetBias: Leveraging Debiased Data for Tuning EvaluatorsFindings of the Association for Computational LinguisticsJunsoo Park, Seungyeon Jwa, Ren Meiying, et al.2024 · 67 citations
  21. Crawling the Internal Knowledge-Base of Language ModelsFindings of the Association for Computational LinguisticsRoi Cohen, Mor Geva, Jonathan Berant, et al.2023 · 67 citations
  22. Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank ModificationsarXiv:2402.05162Boyi Wei, Kaixuan Huang, Yangsibo Huang, et al.2024 · 66 citations
  23. JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak AttacksarXiv:2404.03027Weidi Luo, Siyuan Ma, Xiaogeng Liu, et al.2024 · 66 citations
  24. Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language ModelsFindings of the Association for Computational LinguisticsAlfonso Amayuelas, Kyle Wong, Liangming Pan, et al.2024 · 66 citations
  25. Inference-Time Scaling for Generalist Reward ModelingarXiv:2504.02495Zijun Liu, Peiyi Wang, Runxin Xu, et al.2025 · 65 citations
  26. A Comprehensive Survey on Long Context Language ModelingarXiv:2503.17407Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.2025 · 64 citations
  27. Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-JudgeConference on Empirical Methods in Natural Language Processing (EMNLP)Tianhao Wu, Weizhe Yuan, Olga Golovneva, et al.2025 · 64 citations
  28. What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt EngineeringConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Federico Errica, Davide Sanvito, Giuseppe Siracusano, et al.2025 · 63 citations
  29. Self-Distillation Bridges Distribution Gap in Language Model Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Zhaorui Yang, Tianyu Pang, Haozhe Feng, et al.2024 · 63 citations
  30. 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
  31. Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language ModelsarXiv:2402.02207Yongshuo Zong, Ondrej Bohdal, Tingyang Yu, et al.2024 · 60 citations
  32. Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task ArithmeticAnnual Meeting of the Association for Computational Linguistics (ACL)Rishabh Bhardwaj, Duc Anh Do, Soujanya Poria2024 · 59 citations
  33. MAPO: Advancing Multilingual Reasoning through Multilingual-Alignment-as-Preference OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Shuaijie She, Wei Zou, Shujian Huang, et al.2024 · 59 citations
  34. Rho-1: Not All Tokens Are What You NeedarXiv:2404.07965Zhenghao Lin, Zhibin Gou, Yeyun Gong, et al.2024 · 59 citations
  35. Simple linear attention language models balance the recall-throughput tradeoffarXiv:2402.18668Simran Arora, Sabri Eyuboglu, Michael Zhang, et al.2024 · 59 citations
  36. MLLM-Protector: Ensuring MLLM's Safety without Hurting PerformanceConference on Empirical Methods in Natural Language Processing (EMNLP)Renjie Pi, Tianyang Han, Jianshu Zhang, et al.2024 · 58 citations
  37. Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in ChinchillaarXiv:2307.09458Tom Lieberum, Matthew Rahtz, Janos Kramar, et al.2023 · 58 citations
  38. LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuningarXiv:2308.03303Longteng Zhang, Lin Zhang, Shaohuai Shi, et al.2023 · 58 citations
  39. Dialect prejudice predicts AI decisions about people's character, employability, and criminalityarXiv:2403.00742Valentin Hofmann, Pratyusha Ria Kalluri, Dan Jurafsky, et al.2024 · 57 citations
  40. TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful SpaceAnnual Meeting of the Association for Computational Linguistics (ACL)Shaolei Zhang, Tian Yu, Yang Feng2024 · 57 citations
  41. Unintended Impacts of LLM Alignment on Global RepresentationAnnual Meeting of the Association for Computational Linguistics (ACL)Michael J Ryan, William Held, Diyi Yang2024 · 57 citations
  42. Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedbackarXiv:2303.05453Hannah Rose Kirk, Bertie Vidgen, Paul Rottger, et al.2023 · 57 citations
  43. Massively Multi-Cultural Knowledge Acquisition & LM BenchmarkingarXiv:2402.09369Yi Fung, Ruining Zhao, Jae Doo, et al.2024 · 56 citations
  44. The Art of Saying No: Contextual Noncompliance in Language ModelsConference on Neural Information Processing Systems (NeurIPS)Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, et al.2024 · 56 citations
  45. Zoology: Measuring and Improving Recall in Efficient Language ModelsarXiv:2312.04927Simran Arora; Sabri Eyuboglu; Aman Timalsina; Isys Johnson; Michael Poli; James Zou; Atri Rudra;, Christopher Re2023 · 55 citations
  46. AEGIS2.0: A Diverse AI Safety Dataset and Risks Taxonomy for Alignment of LLM GuardrailsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Shaona Ghosh, Prasoon Varshney, Makesh Narsimhan Sreedhar, et al.2025 · 53 citations
  47. RM-Bench: Benchmarking Reward Models of Language Models with Subtlety and StylearXiv:2410.16184Yantao Liu, Zijun Yao, Rui Min, et al.2024 · 53 citations
  48. The Learnability of In-Context LearningConference on Neural Information Processing Systems (NeurIPS)Noam Wies, Yoav Levine, Amnon Shashua2023 · 53 citations
  49. SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Zijun Yao, Weijian Qi, Liangming Pan, et al.2025 · 52 citations
  50. LLM Internal States Reveal Hallucination Risk Faced With a QueryarXiv:2407.03282Ziwei Ji, Delong Chen, Etsuko Ishii, et al.2024 · 52 citations
  51. Explore, Establish, Exploit: Red Teaming Language Models from ScratcharXiv:2306.09442Stephen Casper, Jason Lin, Joe Kwon, et al.2023 · 52 citations
  52. MiniMax-01: Scaling Foundation Models with Lightning AttentionarXiv:2501.08313MiniMax, Aonian Li, Bangwei Gong, et al.2025 · 50 citations
  53. Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference FeedbackConference on Neural Information Processing Systems (NeurIPS)Hamish Ivison, Yizhong Wang, Jiacheng Liu, et al.2024 · 50 citations
  54. The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce HarmConference on Empirical Methods in Natural Language Processing (EMNLP)Aakanksha, Arash Ahmadian, Beyza Ermis, et al.2024 · 49 citations
  55. Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI SynergyarXiv:2507.01352Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.2025 · 48 citations
  56. IndicLLMSuite: A Blueprint for Creating Pre-training and Fine-Tuning Datasets for Indian LanguagesAnnual Meeting of the Association for Computational Linguistics (ACL)Mohammed Safi Ur Rahman Khan, Priyam Mehta, Ananth Sankar, et al.2024 · 48 citations
  57. Unfamiliar Finetuning Examples Control How Language Models HallucinateConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Katie Kang, Eric Wallace, Claire Tomlin, et al.2025 · 47 citations
  58. Can Multiple-choice Questions Really Be Useful in Detecting the Abilities of LLMs?Language Resources and Evaluation Conference (LREC)Wangyue Li, Liangzhi Li, Tong Xiang, et al.2024 · 47 citations
  59. Towards Mitigating Hallucination in Large Language Models via Self-ReflectionarXiv:2310.06271Ziwei Ji, Tiezheng Yu, Yan Xu, et al.2023 · 47 citations
  60. ARGS: Alignment as Reward-Guided SearcharXiv:2402.01694Maxim Khanov, Jirayu Burapacheep, Yixuan Li2024 · 46 citations
  61. AlGhafa Evaluation Benchmark for Arabic Language ModelsArabic Natural Language Processing Conference (ArabicNLP)Ebtesam Almazrouei, Ruxandra Cojocaru, Michele Baldo, et al.2023 · 46 citations
  62. Don't throw away your value model! Generating more preferable text with Value-Guided Monte-Carlo Tree Search decodingarXiv:2309.15028Jiacheng Liu, Andrew Cohen, Ramakanth Pasunuru, et al.2023 · 46 citations
  63. Lost in Translation: Large Language Models in Non-English Content AnalysisarXiv:2306.07377Gabriel Nicholas, Aliya Bhatia2023 · 45 citations
  64. Understanding Catastrophic Forgetting in Language Models via Implicit InferencearXiv:2309.10105Suhas Kotha, Jacob Mitchell Springer, Aditi Raghunathan2023 · 45 citations
  65. HyperCLOVA X Technical ReportarXiv:2404.01954Kang Min Yoo, Jaegeun Han, Sookyo In, et al.2024 · 44 citations
  66. Long-Context Language Modeling with Parallel Context EncodingAnnual Meeting of the Association for Computational Linguistics (ACL)Howard Yen, Tianyu Gao, Danqi Chen2024 · 44 citations
  67. FLIRT: Feedback Loop In-context Red TeamingConference on Empirical Methods in Natural Language Processing (EMNLP)Ninareh Mehrabi, Palash Goyal, Christophe Dupuy, et al.2024 · 42 citations
  68. Goal Driven Discovery of Distributional Differences via Language DescriptionsarXiv:2302.14233Ruiqi Zhong, Peter Zhang, Steve Li, et al.2023 · 42 citations
  69. Paloma: A Benchmark for Evaluating Language Model FitConference on Neural Information Processing Systems (NeurIPS)Ian Magnusson, Akshita Bhagia, Valentin Hofmann, et al.2023 · 42 citations
  70. When does In-context Learning Fall Short and Why? A Study on Specification-Heavy TasksarXiv:2311.08993Hao Peng, Xiaozhi Wang, Jianhui Chen, et al.2023 · 42 citations
  71. Transcending Scaling Laws with 0.1% Extra ComputearXiv:2210.11399Yi Tay, Jason Wei, Hyung Won Chung, et al.2022 · 42 citations
  72. MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment TasksConference on Neural Information Processing Systems (NeurIPS)Allen Nie, Yuhui Zhang, Atharva Amdekar, et al.2023 · 41 citations
  73. SALMON: Self-Alignment with Instructable Reward ModelsarXiv:2310.05910Zhiqing Sun, Yikang Shen, Hongxin Zhang, et al.2023 · 41 citations
  74. The MiniPile Challenge for Data-Efficient Language ModelsarXiv:2304.08442Jean Kaddour2023 · 41 citations
  75. Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words?Conference on Empirical Methods in Natural Language Processing (EMNLP)Gal Yona, Roee Aharoni, Mor Geva2024 · 40 citations
  76. Observational Scaling Laws and the Predictability of Language Model PerformancearXiv:2405.10938Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto2024 · 40 citations
  77. Aligning Language Models with Preferences through f-divergence MinimizationarXiv:2302.08215Dongyoung Go, Tomasz Korbak, German Kruszewski, et al.2023 · 39 citations
  78. CulturalBench: A Robust, Diverse and Challenging Benchmark for Measuring LMs' Cultural Knowledge Through Human-AI Red-TeamingAnnual Meeting of the Association for Computational Linguistics (ACL)Yu Ying Chiu, Liwei Jiang, Bill Yuchen Lin, et al.2025 · 38 citations
  79. Introducing v0.5 of the AI Safety Benchmark from MLCommonsarXiv:2404.12241Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.2024 · 38 citations
  80. Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling ApproachesFindings of the Association for Computational LinguisticsDaniel Fried, Nicholas Tomlin, Jennifer Hu, et al.2023 · 38 citations
  81. Aligning Large Language Models with Human Preferences through Representation EngineeringAnnual Meeting of the Association for Computational Linguistics (ACL)Wenhao Liu, Xiaohua Wang, Muling Wu, et al.2024 · 37 citations
  82. DeAL: Decoding-time Alignment for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)James Y. Huang, Sailik Sengupta, Daniele Bonadiman, et al.2025 · 36 citations
  83. An Emulator for Fine-Tuning Large Language Models using Small Language ModelsarXiv:2310.12962Eric Mitchell, Rafael Rafailov, Archit Sharma, et al.2023 · 36 citations
  84. Benchmarking Distributional Alignment of Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Nicole Meister, Carlos Guestrin, Tatsunori Hashimoto2025 · 35 citations
  85. Direct Judgement Preference OptimizationConference on Empirical Methods in Natural Language Processing (EMNLP)PeiFeng Wang, Austin Xu, Yilun Zhou, et al.2025 · 35 citations
  86. ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world ScenariosInternational Conference on Computational Linguistics (COLING)Junjie Ye, Guanyu Li, SongYang Gao, et al.2025 · 35 citations
  87. Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language ModelsarXiv:2305.09955Shangbin Feng, Weijia Shi, Yuyang Bai, et al.2023 · 35 citations
  88. Through the Lens of Core Competency: Survey on Evaluation of Large Language ModelsarXiv:2308.07902Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.2023 · 35 citations
  89. Qwen3Guard Technical ReportarXiv:2510.14276Haiquan Zhao, Chenhan Yuan, Fei Huang, et al.2025 · 33 citations
  90. SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model SafetyarXiv:2404.05399Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.2024 · 33 citations
  91. BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language ModelsarXiv:2309.06085Wei Qi Leong, Jian Gang Ngui, Yosephine Susanto, et al.2023 · 33 citations
  92. Interpretable Unified Language CheckingarXiv:2304.03728Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang, et al.2023 · 32 citations
  93. LiPO: Listwise Preference Optimization through Learning-to-RankConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Tianqi Liu, Zhen Qin, Junru Wu, et al.2025 · 31 citations
  94. Airavata: Introducing Hindi Instruction-tuned LLMarXiv:2401.15006Jay Gala, Thanmay Jayakumar, Jaavid Aktar Husain, et al.2024 · 31 citations
  95. Knowledge Boundary of Large Language Models: A SurveyAnnual Meeting of the Association for Computational Linguistics (ACL)Moxin Li, Yong Zhao, Wenxuan Zhang, et al.2025 · 30 citations
  96. RMB: Comprehensively Benchmarking Reward Models in LLM AlignmentarXiv:2410.09893Enyu Zhou, Guodong Zheng, Binghai Wang, et al.2024 · 30 citations
  97. Measuring and Modifying Factual Knowledge in Large Language ModelsarXiv:2306.06264Pouya Pezeshkpour2023 · 30 citations
  98. Rigorously Assessing Natural Language Explanations of NeuronsBlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLPJing Huang, Atticus Geiger, Karel D'Oosterlinck, et al.2023 · 30 citations
  99. The Quantization Model of Neural ScalingarXiv:2303.13506Eric J. Michaud, Ziming Liu, Uzay Girit, et al.2023 · 30 citations
  100. Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red TeamingarXiv:2501.18837Mrinank Sharma, Meg Tong, Jesse Mu, et al.2025 · 29 citations

1 2 3 4 5 … 8

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/tom-conerly/cited-by/page/4/