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Who cites Ishita Dasgupta

3,833 citations of their works from 3,616 papers of our library (of the 149,439 whose bibliographies we read) · 884 with a page here, the most cited first · page 1 of 9 · 1–100 · ← Ishita Dasgupta

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  1. Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsarXiv:2201.11903Jason Wei, Xuezhi Wang, Dale Schuurmans, et al.2022 · 11,499 citations
  2. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
  3. A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open QuestionsACM Transactions on Information SystemsLei Huang, Weijiang Yu, Weitao Ma, et al.2023 · 3,231 citations
  4. Emergent Abilities of Large Language ModelsarXiv:2206.07682Jason Wei, Yi Tay, Rishi Bommasani, et al.2022 · 2,269 citations
  5. DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language ModelsarXiv:2402.03300Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.2024 · 2,115 citations
  6. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextarXiv:2403.05530Gemini Team, Petko Georgiev, Ving Ian Lei, et al.2024 · 1,589 citations
  7. 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
  8. 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
  9. Phi-3 Technical Report: A Highly Capable Language Model Locally on Your PhonearXiv:2404.14219Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.2024 · 1,134 citations
  10. Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve ThemFindings of the Association for Computational LinguisticsMirac Suzgun, Nathan Scales, Nathanael Schärli, et al.2023 · 1,119 citations
  11. Qwen2.5-VL Technical ReportarXiv:2502.13923Shuai Bai, Keqin Chen, Xuejing Liu, et al.2025 · 1,031 citations
  12. MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGIIEEE Computer Society Conference on Computer Vision and Pattern RecognitionXiang Yue, Yuansheng Ni, Kai Zhang, et al.2023 · 1,005 citations
  13. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic CapabilitiesarXiv:2507.06261Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.2025 · 974 citations
  14. MMBench: Is Your Multi-modal Model an All-around Player?Lecture notes in computer scienceYuan Liu, Haodong Duan, Yuanhan Zhang, et al.2023 · 942 citations
  15. Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any ResolutionarXiv:2409.12191Peng Wang, Shuai Bai, Sinan Tan, et al.2024 · 860 citations
  16. Explainability for Large Language Models: A SurveyACM Transactions on Intelligent Systems and TechnologyHaiyan Zhao, Hanjie Chen, Fan Yang, et al.2023 · 790 citations
  17. Towards Reasoning in Large Language Models: A SurveyFindings of the Association for Computational LinguisticsJie Huang, Kevin Chen-Chuan Chang2023 · 780 citations
  18. STaR: Bootstrapping Reasoning With ReasoningEric Zelikman, Yuhuai Wu, Jesse Mu, et al.2022 · 777 citations
  19. 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
  20. Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context LearningConference on Neural Information Processing Systems (NeurIPS)Haokun Liu, Derek Tam, Mohammed Muqeeth, et al.2022 · 754 citations
  21. SGLang: Efficient Execution of Structured Language Model ProgramsConference on Neural Information Processing Systems (NeurIPS)Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, et al.2023 · 729 citations
  22. 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
  23. 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
  24. LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for CodearXiv:2403.07974Naman Jain, King Han, Alex Gu, et al.2024 · 578 citations
  25. Large Language Models Can Self-ImproveConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaxin Huang, Shixiang Gu, Le Hou, et al.2023 · 575 citations
  26. Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model ParametersarXiv:2408.03314Charlie Snell, Jaehoon Lee, Kelvin Xu, et al.2024 · 567 citations
  27. Jailbreaking Black Box Large Language Models in Twenty QueriesarXiv:2310.08419Patrick Chao, Alexander Robey, Edgar Dobriban, et al.2023 · 553 citations
  28. Chatbot Arena: An Open Platform for Evaluating LLMs by Human PreferencearXiv:2403.04132Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, et al.2024 · 546 citations
  29. How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source SuitesScience China Information SciencesZhe Chen, Weiyun Wang, Hao Tian, et al.2024 · 541 citations
  30. Unleashing the potential of prompt engineering for large language modelsarXiv:2310.14735 · Patterns 6(6) 101,260 (2025)Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.2023 · 536 citations
  31. LLaVA-OneVision: Easy Visual Task TransferarXiv:2408.03326Bo Li, Yuanhan Zhang, Dong Guo, et al.2024 · 477 citations
  32. MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual ContextsarXiv:2310.02255Pan Lu, Hritik Bansal, Tony Xia, et al.2023 · 468 citations
  33. OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific ProblemsAnnual Meeting of the Association for Computational Linguistics (ACL)Chaoqun He, Renjie Luo, Yuzhuo Bai, et al.2024 · 456 citations
  34. FinGPT: Open-Source Financial Large Language ModelsarXiv:2306.06031Hongyang Yang, Xiao-Yang Liu, Christina Dan Wang2023 · 445 citations
  35. Kimi k1.5: Scaling Reinforcement Learning with LLMsarXiv:2501.12599Kimi Team, Angang Du, Bofei Gao, et al.2025 · 431 citations
  36. 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
  37. Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingarXiv:2411.15124Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024 · 423 citations
  38. 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
  39. Yi: Open Foundation Models by 01.AIarXiv:2403.04652Alex Young, Bei Chen, Chao Li, et al.2024 · 408 citations
  40. Do Prompt-Based Models Really Understand the Meaning of Their Prompts?Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Albert Webson, Ellie Pavlick2022 · 407 citations
  41. RULER: What's the Real Context Size of Your Long-Context Language Models?arXiv:2404.06654Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, et al.2024 · 400 citations
  42. VILA: On Pre-training for Visual Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionJi Lin, Hongxu Yin, Wei Ping, et al.2023 · 381 citations
  43. The AI Scientist: Towards Fully Automated Open-Ended Scientific DiscoveryarXiv:2408.06292Chris Lu, Cong Lu, Robert Tjarko Lange, et al.2024 · 372 citations
  44. WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-InstructarXiv:2308.09583Haipeng Luo, Qingfeng Sun, Can Xu, et al.2023 · 372 citations
  45. Augmented Language Models: a SurveyarXiv:2302.07842Grégoire Mialon, Roberto Dessì, Maria Lomeli, et al.2023 · 369 citations
  46. 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
  47. SnapKV: LLM Knows What You are Looking for Before GenerationConference on Neural Information Processing Systems (NeurIPS)Yuhong Li, Yingbing Huang, Bowen Yang, et al.2024 · 355 citations
  48. HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionTianrui Guan, Fuxiao Liu, Xiyang Wu, et al.2023 · 335 citations
  49. HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust RefusalarXiv:2402.04249Mantas Mazeika, Long Phan, Xuwang Yin, et al.2024 · 330 citations
  50. 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
  51. MM-LLMs: Recent Advances in MultiModal Large Language ModelsFindings of the Association for Computational LinguisticsDuzhen Zhang, Yahan Yu, Jiahua Dong, et al.2024 · 320 citations
  52. Multimodal Chain-of-Thought Reasoning in Language ModelsarXiv:2302.00923Zhuosheng Zhang, Aston Zhang, Mu Li, et al.2023 · 308 citations
  53. OCRBench: On the Hidden Mystery of OCR in Large Multimodal ModelsScience China Information SciencesYuliang Liu, Zhang Li, Mingxin Huang, et al.2023 · 306 citations
  54. xLSTM: Extended Long Short-Term MemoryConference on Neural Information Processing Systems (NeurIPS)Maximilian Beck, Korbinian Pöppel, Markus Spanring, et al.2024 · 296 citations
  55. Text Classification via Large Language ModelsFindings of the Association for Computational LinguisticsXiaofei Sun, Xiaoya Li, Jiwei Li, et al.2023 · 292 citations
  56. Large Language Model based Multi-Agents: A Survey of Progress and ChallengesarXiv:2402.01680Taicheng Guo, Xiuying Chen, Yaqi Wang, et al.2024 · 288 citations
  57. Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271Zhe Chen, Weiyun Wang, Yue Cao, et al.2024 · 287 citations
  58. An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language ModelsLecture notes in computer scienceLiang Chen, Haozhe Zhao, Tianyu Liu, et al.2024 · 279 citations
  59. Are We on the Right Way for Evaluating Large Vision-Language Models?Conference on Neural Information Processing Systems (NeurIPS)Lin Chen, Jinsong Li, Xiaoyi Dong, et al.2024 · 277 citations
  60. GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language ModelsarXiv:2410.05229Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.2024 · 273 citations
  61. MiniCPM-V: A GPT-4V Level MLLM on Your PhonearXiv:2408.01800Yuan Yao, Tianyu Yu, Ao Zhang, et al.2024 · 269 citations
  62. MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training StrategiesarXiv:2404.06395Shengding Hu, Yuge Tu, Xu Han, et al.2024 · 269 citations
  63. HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Bernal Jimenez Gutierrez, Yiheng Shu, Yu Gu, et al.2024 · 268 citations
  64. OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer EnvironmentsConference on Neural Information Processing Systems (NeurIPS)Tianbao Xie, Danyang Zhang, Jixuan Chen, et al.2024 · 264 citations
  65. The Effect of Sampling Temperature on Problem Solving in Large Language ModelsFindings of the Association for Computational LinguisticsMatthew Renze2024 · 263 citations
  66. Large Language Models for Data Annotation and Synthesis: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Zhen Tan, Dawei Li, Song Wang, et al.2024 · 262 citations
  67. Humanity's Last ExamNatureLong Phan, Alice Gatti, Ziwen Han, et al.2025 · 256 citations
  68. InternVideo2: Scaling Foundation Models for Multimodal Video UnderstandingLecture notes in computer scienceYi Wang, Kunchang Li, Xinhao Li, et al.2024 · 253 citations
  69. Language Models can Solve Computer TasksConference on Neural Information Processing Systems (NeurIPS)Geunwoo Kim, Pierre Baldi, Stephen McAleer2023 · 249 citations
  70. KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV CachearXiv:2402.02750Zirui Liu, Jiayi Yuan, Hongye Jin, et al.2024 · 244 citations
  71. Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-ThoughtarXiv:2210.01240Abulhair Saparov, He He2022 · 244 citations
  72. Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive SurveyarXiv:2403.14608Zeyu Han, Chao Gao, Jinyang Liu, et al.2024 · 240 citations
  73. Qwen2-Audio Technical ReportarXiv:2407.10759Yunfei Chu, Jin Xu, Qian Yang, et al.2024 · 238 citations
  74. MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?Lecture notes in computer scienceRenrui Zhang, Dongzhi Jiang, Yichi Zhang, et al.2024 · 232 citations
  75. Qwen2.5-Omni Technical ReportarXiv:2503.20215Jin Xu, Zhifang Guo, Jinzheng He, et al.2025 · 227 citations
  76. NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding ModelsarXiv:2405.17428Chankyu Lee, Rajarshi Roy, Mengyao Xu, et al.2024 · 222 citations
  77. OpenHands: An Open Platform for AI Software Developers as Generalist AgentsarXiv:2407.16741Xingyao Wang, Boxuan Li, Yufan Song, et al.2024 · 221 citations
  78. FOLIO: Natural Language Reasoning with First-Order LogicarXiv:2209.00840Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al.2022 · 219 citations
  79. Maieutic Prompting: Logically Consistent Reasoning with Recursive ExplanationsConference on Empirical Methods in Natural Language Processing (EMNLP)Jaehun Jung, Lianhui Qin, Sean Welleck, et al.2022 · 219 citations
  80. Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mosh Levy, Alon Jacoby, Yoav Goldberg2024 · 217 citations
  81. Making Language Models Better Reasoners with Step-Aware VerifierAnnual Meeting of the Association for Computational Linguistics (ACL)Yifei Li, Zeqi Lin, Shizhuo Zhang, et al.2023 · 217 citations
  82. 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
  83. 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
  84. What matters when building vision-language models?Conference on Neural Information Processing Systems (NeurIPS)Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.2024 · 212 citations
  85. Sources of Hallucination by Large Language Models on Inference TasksFindings of the Association for Computational LinguisticsNick McKenna, Tianyi Li, Liang Cheng, et al.2023 · 212 citations
  86. PersonaLLM: Investigating the Ability of Large Language Models to Express Personality TraitsFindings of the Association for Computational LinguisticsHang Jiang, Xiajie Zhang, Xubo Cao, et al.2023 · 211 citations
  87. 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
  88. What Can Transformers Learn In-Context? A Case Study of Simple Function ClassesConference on Neural Information Processing Systems (NeurIPS)Shivam Garg, Dimitris Tsipras, Percy Liang, et al.2022 · 209 citations
  89. DeepSeek-VL: Towards Real-World Vision-Language UnderstandingarXiv:2403.05525Haoyu Lu, Wen Liu, Bo Zhang, et al.2024 · 208 citations
  90. BLINK: Multimodal Large Language Models Can See but Not PerceiveLecture notes in computer scienceXingyu Fu, Yushi Hu, Bangzheng Li, et al.2024 · 206 citations
  91. Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Oded Ovadia, Menachem Brief, Moshik Mishaeli, et al.2024 · 206 citations
  92. Measuring Multimodal Mathematical Reasoning with MATH-Vision DatasetConference on Neural Information Processing Systems (NeurIPS)Ke Wang, Junting Pan, Weikang Shi, et al.2024 · 203 citations
  93. MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse AttentionConference on Neural Information Processing Systems (NeurIPS)Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, et al.2024 · 202 citations
  94. ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree SearchConference on Neural Information Processing Systems (NeurIPS)Dan Zhang, Sining Zhoubian, Ziniu Hu, et al.2024 · 200 citations
  95. DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code IntelligencearXiv:2406.11931DeepSeek-AI, Qihao Zhu, Daya Guo, et al.2024 · 196 citations
  96. The Unreliability of Explanations in Few-shot Prompting for Textual ReasoningConference on Neural Information Processing Systems (NeurIPS)Xi Ye, Greg Durrett2022 · 196 citations
  97. Tool Learning with Large Language Models: A SurveyFrontiers of Computer ScienceChangle Qu, Sunhao Dai, Xiaochi Wei, et al.2024 · 195 citations
  98. LLM in a flash: Efficient Large Language Model Inference with Limited MemoryAnnual Meeting of the Association for Computational Linguistics (ACL)Keivan Alizadeh, Seyed Iman Mirzadeh, Dmitry Belenko, et al.2024 · 193 citations
  99. WebVoyager: Building an End-to-End Web Agent with Large Multimodal ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Hongliang He, Wenlin Yao, Kaixin Ma, et al.2024 · 191 citations
  100. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesarXiv:2406.06608Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 189 citations

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