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Who cites Jan Kocon

1,601 citations of their works from 1,569 papers of our library (of the 149,439 whose bibliographies we read) · 358 with a page here, the most cited first · page 2 of 4 · 101–200 · ← Jan Kocon

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  1. DataComp-LM: In search of the next generation of training sets for language modelsConference on Neural Information Processing Systems (NeurIPS)Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.2024 · 191 citations
  2. LawBench: Benchmarking Legal Knowledge of Large Language ModelsarXiv:2309.16289Zhiwei Fei, Xiaoyu Shen, Dawei Zhu, et al.2023 · 186 citations
  3. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 182 citations
  4. LILA: A Unified Benchmark for Mathematical ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Swaroop Mishra, Matthew Finlayson, Pan Lu, et al.2022 · 179 citations
  5. KernelBench: Can LLMs Write Efficient GPU Kernels?arXiv:2502.10517Anne Ouyang, Simon Guo, Simran Arora, et al.2025 · 178 citations
  6. Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMsConference of the European Chapter of the Association for Computational Linguistics (EACL)Simone Balloccu, Patrícia Schmidtová, Mateusz Lango, et al.2024 · 174 citations
  7. AI Alignment: A Comprehensive SurveyarXiv:2310.19852Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.2023 · 173 citations
  8. Generative Representational Instruction TuningarXiv:2402.09906Niklas Muennighoff, Hongjin Su, Liang Wang, et al.2024 · 172 citations
  9. LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic ProversConference on Empirical Methods in Natural Language Processing (EMNLP)Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.2023 · 172 citations
  10. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 171 citations
  11. ShortGPT: Layers in Large Language Models are More Redundant Than You ExpectarXiv:2403.03853Xin Men, Mingyu Xu, Qingyu Zhang, et al.2024 · 170 citations
  12. From System 1 to System 2: A Survey of Reasoning Large Language ModelsarXiv:2502.17419Zhong-Zhi Li, Duzhen Zhang, Ming-Liang Zhang, et al.2025 · 165 citations
  13. LooGLE: Can Long-Context Language Models Understand Long Contexts?Annual Meeting of the Association for Computational Linguistics (ACL)Jiaqi Li, Mengmeng Wang, Zilong Zheng, et al.2023 · 165 citations
  14. Orca 2: Teaching Small Language Models How to ReasonarXiv:2311.11045Arindam Mitra, Luciano Del Corro, Shweti Mahajan, et al.2023 · 162 citations
  15. LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt CompressionFindings of the Association for Computational LinguisticsZhuoshi Pan, Qianhui Wu, Huiqiang Jiang, et al.2024 · 161 citations
  16. L-Eval: Instituting Standardized Evaluation for Long Context Language ModelsarXiv:2307.11088Chenxin An, Shansan Gong, Ming Zhong, et al.2023 · 161 citations
  17. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
  18. ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Justin Chen, Swarnadeep Saha, Mohit Bansal2024 · 156 citations
  19. 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
  20. Self-Evaluation Guided Beam Search for ReasoningConference on Neural Information Processing Systems (NeurIPS)Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.2023 · 149 citations
  21. Language Model Behavior: A Comprehensive SurveyComputational LinguisticsTyler A. Chang, Benjamin K. Bergen2024 · 148 citations
  22. A Roadmap to Pluralistic AlignmentarXiv:2402.05070Taylor Sorensen, Jared Moore, Jillian Fisher, et al.2024 · 143 citations
  23. 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
  24. Long-context LLMs Struggle with Long In-context LearningarXiv:2404.02060Tianle Li, Ge Zhang, Quy Duc Do, et al.2024 · 138 citations
  25. 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
  26. 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
  27. 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
  28. 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
  29. 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
  30. 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
  31. 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
  32. Deductive Verification of Chain-of-Thought ReasoningConference on Neural Information Processing Systems (NeurIPS)Zhan Ling, Yunhao Fang, Xuanlin Li, et al.2023 · 130 citations
  33. 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
  34. Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-TuningarXiv:2303.15647Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.2023 · 129 citations
  35. 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
  36. Artificial Artificial Artificial Intelligence: Crowd Workers Widely Use Large Language Models for Text Production TasksarXiv:2306.07899Veniamin Veselovsky, Manoel Horta Ribeiro, Robert West2023 · 127 citations
  37. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 124 citations
  38. Large Language Models Understand and Can be Enhanced by Emotional StimuliarXiv:2307.11760Cheng Li, Jindong Wang, Yixuan Zhang, et al.2023 · 116 citations
  39. 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
  40. 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
  41. Evaluating the Performance of Large Language Models on GAOKAO BenchmarkarXiv:2305.12474Xiaotian Zhang, Chunyang Li, Yi Zong, et al.2023 · 109 citations
  42. 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
  43. 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
  44. 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
  45. MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 103 citations
  46. Can we trust the evaluation on ChatGPT?Workshop on Trustworthy NLPRachith Aiyappa, Jisun An, Haewoon Kwak, et al.2023 · 103 citations
  47. 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
  48. FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsarXiv:2307.10928Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.2023 · 100 citations
  49. MAmmoTH2: Scaling Instructions from the WebConference on Neural Information Processing Systems (NeurIPS)Xiang Yue, Tuney Zheng, Ge Zhang, et al.2024 · 96 citations
  50. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 96 citations
  51. INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language ModelsarXiv:2306.04757Yew Ken Chia, Pengfei Hong, Lidong Bing, et al.2023 · 96 citations
  52. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
  53. 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
  54. 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
  55. 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
  56. Exploring the Potential of ChatGPT on Sentence Level Relations: A Focus on Temporal, Causal, and Discourse RelationsFindings of the Association for Computational LinguisticsChunkit Chan, Cheng Jiayang, Weiqi Wang, et al.2024 · 92 citations
  57. 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
  58. 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
  59. “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
  60. How to Train Long-Context Language Models (Effectively)Annual Meeting of the Association for Computational Linguistics (ACL)Tianyu Gao, Alexander Wettig, Howard Yen, et al.2025 · 89 citations
  61. Small Language Models: Survey, Measurements, and InsightsarXiv:2409.15790Zhenyan Lu, Xiang Li, Dongqi Cai, et al.2024 · 88 citations
  62. 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
  63. 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
  64. 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
  65. ORCA: A Challenging Benchmark for Arabic Language UnderstandingFindings of the Association for Computational LinguisticsAbdelRahim Elmadany, ElMoatez Billah Nagoudi, Muhammad Abdul-Mageed2023 · 83 citations
  66. Style Over Substance: Evaluation Biases for Large Language ModelsInternational Conference on Computational Linguistics (COLING)Minghao Wu, Alham Fikri Aji2025 · 81 citations
  67. MoBA: Mixture of Block Attention for Long-Context LLMsConference on Neural Information Processing Systems (NeurIPS)Enzhe Lu, Zhejun Jiang, Jingyuan Liu, et al.2025 · 80 citations
  68. AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Harsh Trivedi, Tushar Khot, Mareike Hartmann, et al.2024 · 80 citations
  69. KoBBQ: Korean Bias Benchmark for Question AnsweringTransactions of the Association for Computational Linguistics (TACL)Jiho Jin, Jiseon Kim, Nayeon Lee, et al.2024 · 78 citations
  70. KMMLU: Measuring Massive Multitask Language Understanding in KoreanConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Guijin Son, Hanwool Lee, Sungdong Kim, et al.2025 · 76 citations
  71. GPTEval: A Survey on Assessments of ChatGPT and GPT-4Language Resources and Evaluation Conference (LREC)Rui Mao, Guanyi Chen, Xulang Zhang, et al.2024 · 75 citations
  72. PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics CapabilitiesSettaluri Sravanthi, Meet Doshi, Pavan Tankala, et al.2024 · 75 citations
  73. INCLUDE: Evaluating Multilingual Language Understanding with Regional KnowledgearXiv:2411.19799Angelika Romanou, Negar Foroutan, Anna Sotnikova, et al.2024 · 74 citations
  74. MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical ReasoningConference on Neural Information Processing Systems (NeurIPS)Shuyue Stella Li, Vidhisha Balachandran, Shangbin Feng, et al.2024 · 74 citations
  75. MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and TasksConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma, et al.2024 · 74 citations
  76. AlignBench: Benchmarking Chinese Alignment of Large Language ModelsarXiv:2311.18743Xiao Liu, Xuanyu Lei, Shengyuan Wang, et al.2023 · 74 citations
  77. Lion: Adversarial Distillation of Proprietary Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Yuxin Jiang, Chunkit Chan, Mingyang Chen, et al.2023 · 70 citations
  78. 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
  79. 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
  80. 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
  81. CMATH: Can Your Language Model Pass Chinese Elementary School Math Test?arXiv:2306.16636Tianwen Wei, Jian Luan, Wei Liu, et al.2023 · 67 citations
  82. MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning AttentionarXiv:2506.13585MiniMax, Aili Chen, Aonian Li, et al.2025 · 66 citations
  83. 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
  84. A Comprehensive Survey on Long Context Language ModelingarXiv:2503.17407Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.2025 · 64 citations
  85. A Peek into Token Bias: Large Language Models Are Not Yet Genuine ReasonersConference on Empirical Methods in Natural Language Processing (EMNLP)Bowen Jiang, Yangxinyu Xie, Zhuoqun Hao, et al.2024 · 64 citations
  86. CValues: Measuring the Values of Chinese Large Language Models from Safety to ResponsibilityarXiv:2307.09705Guohai Xu, Jiayi Liu, Ming Yan, et al.2023 · 64 citations
  87. Leveraging Large Language Models for NLG Evaluation: Advances and ChallengesConference on Empirical Methods in Natural Language Processing (EMNLP)Zhen Li, Xiaohan Xu, Tao Shen, et al.2024 · 63 citations
  88. Exploring the Benefits of Training Expert Language Models over Instruction TuningarXiv:2302.03202Joel Jang, Seungone Kim, Seonghyeon Ye, et al.2023 · 63 citations
  89. Large Language Model Routing with Benchmark DatasetsarXiv:2309.15789Tal Shnitzer, Anthony Ou, Mirian Silva, et al.2023 · 63 citations
  90. 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
  91. Large Language Models Are Not Strong Abstract ReasonersarXiv:2305.19555Gael Gendron, Qiming Bao, Michael Witbrock, et al.2023 · 61 citations
  92. Beyond the Limits: A Survey of Techniques to Extend the Context Length in Large Language ModelsarXiv:2402.02244Xindi Wang, Mahsa Salmani, Parsa Omidi, et al.2024 · 60 citations
  93. BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of Large Language ModelsLanguage Resources and Evaluation Conference (LREC)Zican Dong, Tianyi Tang, Junyi Li, et al.2024 · 59 citations
  94. BIG-Bench Extra HardAnnual Meeting of the Association for Computational Linguistics (ACL)Mehran Kazemi, Bahare Fatemi, Hritik Bansal, et al.2025 · 58 citations
  95. SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Yige Xu, Xu Guo, Zhiwei Zeng, et al.2025 · 58 citations
  96. Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling LawsarXiv:2401.00448Nikhil Sardana, Jacob Portes, Sasha Doubov, et al.2024 · 57 citations
  97. SuperCLUE: A Comprehensive Chinese Large Language Model BenchmarkarXiv:2307.15020Liang Xu, Anqi Li, Lei Zhu, et al.2023 · 57 citations
  98. 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
  99. DARWIN Series: Domain Specific Large Language Models for Natural SciencearXiv:2308.13565Tong Xie, Yuwei Wan, Wei Huang, et al.2023 · 55 citations
  100. 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

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