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Who cites Dimitris Tsipras

4,880 citations of their works from 4,470 papers of our library (of the 149,439 whose bibliographies we read) · 1,202 with a page here, the most cited first · page 1 of 13 · 1–100 · ← Dimitris Tsipras

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  1. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
  2. Judging LLM-as-a-Judge with MT-Bench and Chatbot ArenaConference on Neural Information Processing Systems (NeurIPS)Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.2023 · 4,573 citations
  3. A Survey on Evaluation of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyYupeng Chang, Xu Wang, Jindong Wang, et al.2023 · 3,648 citations
  4. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
  5. QLoRA: Efficient Finetuning of Quantized LLMsConference on Neural Information Processing Systems (NeurIPS)Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, et al.2023 · 2,929 citations
  6. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  7. Evaluating Large Language Models Trained on CodearXiv:2107.03374Mark Chen, Jerry Tworek, Heewoo Jun, et al.2021 · 2,659 citations
  8. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,287 citations
  9. The Rise and Potential of Large Language Model Based Agents: A SurveyScience China Information SciencesZhiheng Xi, Wenxiang Chen, Xin Guo, et al.2023 · 1,272 citations
  10. A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the UglyarXiv:2312.02003Yifan Yao, Jinhao Duan, Kaidi Xu, et al.2023 · 1,186 citations
  11. Generating Natural Language Adversarial ExamplesConference on Empirical Methods in Natural Language Processing (EMNLP)Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, et al.2018 · 1,111 citations
  12. Bias and Fairness in Large Language Models: A SurveyComputational LinguisticsIsabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.2023 · 1,082 citations
  13. Universal and Transferable Adversarial Attacks on Aligned Language ModelsarXiv:2307.15043Andy Zou, Zifan Wang, Nicholas Carlini, et al.2023 · 1,005 citations
  14. PaLM 2 Technical ReportarXiv:2305.10403Rohan Anil, Andrew M. Dai, Orhan Firat, et al.2023 · 1,000 citations
  15. A Survey on In-context LearningarXiv:2301.00234Qingxiu Dong, Lei Li, Damai Dai, et al.2023 · 978 citations
  16. A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and InteractivityarXiv:2302.04023Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, et al.2023 · 882 citations
  17. ChatGPT: Jack of all trades, master of nonearXiv:2302.10724 · Information Fusion 101,861 (2023)Jan Kocon, Igor Cichecki, Oliwier Kaszyca, et al.2023 · 866 citations
  18. Is ChatGPT a General-Purpose Natural Language Processing Task Solver?Conference on Empirical Methods in Natural Language Processing (EMNLP)Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al.2023 · 828 citations
  19. Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and BeyondACM Transactions on Knowledge Discovery from DataJingfeng Yang, Hongye Jin, Ruixiang Tang, et al.2023 · 814 citations
  20. Can Large Language Models Transform Computational Social Science?Computational LinguisticsCaleb Ziems, William Held, Omar Shaikh, et al.2023 · 790 citations
  21. MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding BenchmarkConference on Neural Information Processing Systems (NeurIPS)Yubo Wang, Xueguang Ma, Ge Zhang, et al.2024 · 761 citations
  22. Capabilities of GPT-4 on Medical Challenge ProblemsarXiv:2303.13375Harsha Nori, Nicholas King, Scott Mayer McKinney, et al.2023 · 717 citations
  23. SWE-bench: Can Language Models Resolve Real-World GitHub Issues?arXiv:2310.06770Carlos E. Jimenez, John Yang, Alexander Wettig, et al.2024 · 704 citations
  24. ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All ToolsarXiv:2406.12793Team GLM, Aohan Zeng, Bin Xu, et al.2024 · 691 citations
  25. BloombergGPT: A Large Language Model for FinancearXiv:2303.17564Shijie Wu, Ozan Irsoy, Steven Lu, et al.2023 · 618 citations
  26. Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought PromptingConference on Neural Information Processing Systems (NeurIPS)Miles Turpin, Julian Michael, Ethan Perez, et al.2023 · 586 citations
  27. gpt-oss-120b & gpt-oss-20b Model CardarXiv:2508.10925OpenAI: Sandhini Agarwal, Lama Ahmad, Jason Ai, et al.2025 · 576 citations
  28. Jailbreaking Black Box Large Language Models in Twenty QueriesarXiv:2310.08419Patrick Chao, Alexander Robey, Edgar Dobriban, et al.2023 · 553 citations
  29. Chatbot Arena: An Open Platform for Evaluating LLMs by Human PreferencearXiv:2403.04132Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, et al.2024 · 546 citations
  30. Large Language Models Can Be Easily Distracted by Irrelevant ContextarXiv:2302.00093Freda Shi, Xinyun Chen, Kanishka Misra, et al.2023 · 534 citations
  31. TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with RecommendationarXiv:2305.00447Keqin Bao; Jizhi Zhang; Yang Zhang; Wenjie Wang; Fuli Feng;, Xiangnan He2023 · 531 citations
  32. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 520 citations
  33. Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking AgentsConference on Empirical Methods in Natural Language Processing (EMNLP)Weiwei Sun, Lingyong Yan, Xinyu Ma, et al.2023 · 496 citations
  34. FreeLB: Enhanced Adversarial Training for Natural Language UnderstandingarXiv:1909.11764Chen Zhu, Yu Cheng, Zhe Gan, et al.2019 · 452 citations
  35. The Falcon Series of Open Language ModelsarXiv:2311.16867Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.2023 · 443 citations
  36. Benchmarking Neural Network Robustness to Common Corruptions and PerturbationsarXiv:1903.12261Dan Hendrycks, Thomas Dietterich2019 · 434 citations
  37. AgentBench: Evaluating LLMs as AgentsarXiv:2308.03688Xiao Liu, Hao Yu, Hanchen Zhang, et al.2023 · 432 citations
  38. Kimi k1.5: Scaling Reinforcement Learning with LLMsarXiv:2501.12599Kimi Team, Angang Du, Bofei Gao, et al.2025 · 431 citations
  39. C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation ModelsarXiv:2305.08322Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, et al.2023 · 428 citations
  40. Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video AnalysisIEEE Computer Society Conference on Computer Vision and Pattern RecognitionChaoyou Fu, Yuhan Dai, Yongdong Luo, et al.2024 · 427 citations
  41. Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingarXiv:2411.15124Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024 · 423 citations
  42. Whose Opinions Do Language Models Reflect?arXiv:2303.17548Shibani Santurkar, Esin Durmus, Faisal Ladhak, et al.2023 · 414 citations
  43. BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical DomainsFindings of the Association for Computational LinguisticsYanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.2024 · 409 citations
  44. FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPUarXiv:2303.06865Ying Sheng, Lianmin Zheng, Binhang Yuan, et al.2023 · 402 citations
  45. Llama Guard: LLM-based Input-Output Safeguard for Human-AI ConversationsarXiv:2312.06674Hakan Inan, Kartikeya Upasani, Jianfeng Chi, et al.2023 · 395 citations
  46. LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language ModelsarXiv:2308.11462Neel Guha; Julian Nyarko; Daniel E. Ho; Christopher Re; Adam Chilton; Aditya Narayana; Alex Chohlas-Wood; Austin Peters; Brandon Waldon; Daniel N. Rockmore; Diego Zambrano; Dmitry Talisman; Enam Hoque; Faiz Surani; Frank Fagan; Galit Sarfaty; Gregory M. Dickinson; Haggai Porat; Jason Hegland; Jessica Wu; Joe Nudell; Joel Niklaus; John Nay; Jonathan H. Choi; Kevin Tobia; Margaret Hagan; Megan Ma; Michael Livermore; Nikon Rasumov-Rahe; Nils Holzenberger; Noam Kolt; Peter Henderson; Sean Rehaag; Sharad Goel; Shang Gao; Spencer Williams; Sunny Gandhi; Tom Zur; Varun Iyer;, Zehua Li2023 · 389 citations
  47. CMMLU: Measuring massive multitask language understanding in ChinesearXiv:2306.09212Haonan Li, Yixuan Zhang, Fajri Koto, et al.2023 · 387 citations
  48. Tool Learning with Foundation ModelsACM Computing SurveysYujia Qin, Shengding Hu, Yankai Lin, et al.2023 · 383 citations
  49. Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical ReasoningarXiv:2305.12295Liangming Pan, Alon Albalak, Xinyi Wang, et al.2023 · 374 citations
  50. A Survey on Large Language Models for Code GenerationACM Transactions on Software Engineering and MethodologyJuyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 367 citations
  51. HotFlip: White-Box Adversarial Examples for Text ClassificationAnnual Meeting of the Association for Computational Linguistics (ACL)Javid Ebrahimi, Anyi Rao, Daniel Lowd, et al.2018 · 363 citations
  52. Toxicity in chatgpt: Analyzing persona-assigned language modelsFindings of the Association for Computational LinguisticsAmeet Deshpande, Vishvak Murahari, Tanmay Rajpurohit, et al.2023 · 353 citations
  53. Certified Robustness to Adversarial Word SubstitutionsConference on Empirical Methods in Natural Language Processing (EMNLP)Robin Jia, Aditi Raghunathan, Kerem Göksel, et al.2019 · 340 citations
  54. Large Language Models for Information Retrieval: A SurveyACM Transactions on Information SystemsYutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen2023 · 339 citations
  55. HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust RefusalarXiv:2402.04249Mantas Mazeika, Long Phan, Xuwang Yin, et al.2024 · 330 citations
  56. Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation ModelsarXiv:2506.05176Yanzhao Zhang, Mingxin Li, Dingkun Long, et al.2025 · 322 citations
  57. Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement LearningarXiv:2503.09516Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.2025 · 322 citations
  58. How Far Can Camels Go? Exploring the State of Instruction Tuning on Open ResourcesConference on Neural Information Processing Systems (NeurIPS)Yizhong Wang, Hamish Ivison, Pradeep Dasigi, et al.2023 · 317 citations
  59. MEDITRON-70B: Scaling Medical Pretraining for Large Language ModelsarXiv:2311.16079Zeming Chen, Alejandro Hernandez Cano, Angelika Romanou, et al.2023 · 315 citations
  60. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
  61. Large Language Models are Effective Text Rankers with Pairwise Ranking PromptingFindings of the Association for Computational LinguisticsZhen Qin, Rolf Jagerman, Kai Hui, et al.2024 · 300 citations
  62. xLSTM: Extended Long Short-Term MemoryConference on Neural Information Processing Systems (NeurIPS)Maximilian Beck, Korbinian Pöppel, Markus Spanring, et al.2024 · 296 citations
  63. Larger language models do in-context learning differentlyarXiv:2303.03846Jerry Wei, Jason Wei, Yi Tay, et al.2023 · 285 citations
  64. MEGA: Multilingual Evaluation of Generative AIarXiv:2303.12528Kabir Ahuja, Harshita Diddee, Rishav Hada, et al.2023 · 285 citations
  65. Prometheus: Inducing Fine-grained Evaluation Capability in Language ModelsarXiv:2310.08491Seungone Kim, Jamin Shin, Yejin Cho, et al.2023 · 281 citations
  66. Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What MattersAnnual Meeting of the Association for Computational Linguistics (ACL)Boshi Wang, Sewon Min, Xiang Deng, et al.2023 · 272 citations
  67. Hallucination-Free? Assessing the Reliability of Leading AI Legal Research ToolsarXiv:2405.20362Varun Magesh, Faiz Surani, Matthew Dahl, et al.2024 · 271 citations
  68. Towards Measuring the Representation of Subjective Global Opinions in Language ModelsarXiv:2306.16388Esin Durmus, Karina Nguyen, Thomas I. Liao, et al.2023 · 270 citations
  69. RedPajama: an Open Dataset for Training Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Maurice Weber, Daniel Fu, Quentin Anthony, et al.2024 · 260 citations
  70. 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
  71. 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
  72. Personality Traits in Large Language ModelsarXiv:2307.00184Greg Serapio-Garcia, Mustafa Safdari, Clement Crepy, et al.2023 · 252 citations
  73. Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and ToxicityarXiv:2301.12867Terry Yue Zhuo, Yujin Huang, Chunyang Chen, et al.2023 · 249 citations
  74. Transformers learn in-context by gradient descentarXiv:2212.07677Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, et al.2022 · 247 citations
  75. Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Myra Cheng, Esin Durmus, Dan Jurafsky2023 · 246 citations
  76. 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
  77. OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of GeneralizationarXiv:2212.12017Srinivasan Iyer, Xi Victoria Lin, Ramakanth Pasunuru, et al.2022 · 244 citations
  78. Visual Adversarial Examples Jailbreak Aligned Large Language ModelsProceedings of the AAAI Conference on Artificial IntelligenceXiangyu Qi, Kaixuan Huang, Ashwinee Panda, et al.2023 · 240 citations
  79. Towards Robust Neural Machine TranslationAnnual Meeting of the Association for Computational Linguistics (ACL)Yong Cheng, Zhaopeng Tu, Fandong Meng, et al.2018 · 238 citations
  80. TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
  81. Baseline Defenses for Adversarial Attacks Against Aligned Language ModelsarXiv:2309.00614Neel Jain, Avi Schwarzschild, Yuxin Wen, et al.2023 · 236 citations
  82. What learning algorithm is in-context learning? Investigations with linear modelsarXiv:2211.15661Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al.2022 · 236 citations
  83. GAIA: a benchmark for General AI AssistantsarXiv:2311.12983Gregoire Mialon, Clementine Fourrier, Craig Swift, et al.2023 · 232 citations
  84. Scalable agent alignment via reward modeling: a research directionarXiv:1811.07871Jan Leike, David Krueger, Tom Everitt, et al.2018 · 227 citations
  85. Accelerating scientific discovery with Co-ScientistNatureJuraj Gottweis, Wei-Hung Weng, Alexander Daryin, et al.2025 · 224 citations
  86. Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought PromptingarXiv:2305.07004Haoyang Huang, Tianyi Tang, Dongdong Zhang, et al.2023 · 224 citations
  87. 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
  88. On Adversarial Examples for Character-Level Neural Machine TranslationInternational Conference on Computational Linguistics (COLING)Javid Ebrahimi, Daniel Lowd, Dejing Dou2018 · 223 citations
  89. AlpaGasus: Training A Better Alpaca with Fewer DataarXiv:2307.08701Lichang Chen, Shiyang Li, Jun Yan, et al.2023 · 220 citations
  90. Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?arXiv:2504.13837 · NeurIPS 2025 Oral; ICML 2025 AI4MATH workshop best paperYang Yue, Zhiqi Chen, Rui Lu, et al.2025 · 216 citations
  91. InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal ModelsarXiv:2504.10479Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.2025 · 216 citations
  92. Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionMatt Deitke, Christopher Clark, Sangho Lee, et al.2024 · 216 citations
  93. Combating Misinformation in the Age of LLMs: Opportunities and ChallengesAI MagazineCanyu Chen, Kai Shu2023 · 214 citations
  94. Search-o1: Agentic Search-Enhanced Large Reasoning ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Xiaoxi Li, Guanting Dong, Jiajie Jin, et al.2025 · 211 citations
  95. From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder PipelinearXiv:2406.11939Tianle Li, Wei-Lin Chiang, Evan Frick, et al.2024 · 210 citations
  96. LIMO: Less is More for ReasoningarXiv:2502.03387Yixin Ye, Zhen Huang, Yang Xiao, et al.2025 · 209 citations
  97. Exploring Human-Like Translation Strategy with Large Language ModelsTransactions of the Association for Computational Linguistics (TACL)Zhiwei He, Tian Liang, Wenxiang Jiao, et al.2024 · 207 citations
  98. Large Language Model as Attributed Training Data Generator: A Tale of Diversity and BiasConference on Neural Information Processing Systems (NeurIPS)Yue Yu, Yuchen Zhuang, Jieyu Zhang, et al.2023 · 202 citations
  99. A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and ValidationArtificial Intelligence ReviewXiaowei Huang, Wenjie Ruan, Wei Huang, et al.2023 · 199 citations
  100. 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

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