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Who cites Melody Y. Guan

1,718 citations of their works from 1,644 papers of our library (of the 149,439 whose bibliographies we read) · 433 with a page here, the most cited first · page 1 of 5 · 1–100 · ← Melody Y. Guan

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  1. Designing Network Design SpacesIEEE Computer Society Conference on Computer Vision and Pattern RecognitionIlija Radosavovic, Raj Prateek Kosaraju, Ross Girshick, et al.2020 · 2,040 citations
  2. FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture SearchIEEE Computer Society Conference on Computer Vision and Pattern RecognitionBichen Wu, Xiaoliang Dai, Peizhao Zhang, et al.2018 · 1,405 citations
  3. OpenAI o1 System CardarXiv:2412.16720OpenAI, Aaron Jaech, Adam Kalai, et al.2024 · 1,110 citations
  4. Progressive Differentiable Architecture Search: Bridging the Depth Gap between Search and EvaluationIEEE/CVF International Conference on Computer Vision (ICCV)Xin Chen, Lingxi Xie, Jun Wu, et al.2019 · 732 citations
  5. gpt-oss-120b & gpt-oss-20b Model CardarXiv:2508.10925OpenAI: Sandhini Agarwal, Lama Ahmad, Jason Ai, et al.2025 · 576 citations
  6. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 520 citations
  7. ProxylessNAS: Direct Neural Architecture Search on Target Task and HardwarearXiv:1812.00332Han Cai, Ligeng Zhu, Song Han2018 · 479 citations
  8. Kimi k1.5: Scaling Reinforcement Learning with LLMsarXiv:2501.12599Kimi Team, Angang Du, Bofei Gao, et al.2025 · 431 citations
  9. Carbon Emissions and Large Neural Network TrainingarXiv:2104.10350David Patterson, Joseph Gonzalez, Quoc Le, et al.2021 · 323 citations
  10. 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
  11. HAT: Hardware-Aware Transformers for Efficient Natural Language ProcessingAnnual Meeting of the Association for Computational Linguistics (ACL)Hanrui Wang, Zhanghao Wu, Zhijian Liu, et al.2020 · 294 citations
  12. OpenAI GPT-5 System CardarXiv:2601.03267Aaditya Singh, Adam Fry, Adam Perelman, et al.2025 · 279 citations
  13. Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency AnalysisACM Computing Surveys 2019Tal Ben-Nun, Torsten Hoefler2018 · 275 citations
  14. Accelerating scientific discovery with Co-ScientistNatureJuraj Gottweis, Wei-Hung Weng, Alexander Daryin, et al.2025 · 224 citations
  15. 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
  16. 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
  17. LIMO: Less is More for ReasoningarXiv:2502.03387Yixin Ye, Zhen Huang, Yang Xiao, et al.2025 · 209 citations
  18. Automated Concatenation of Embeddings for Structured PredictionAnnual Meeting of the Association for Computational Linguistics (ACL)Xinyu Wang, Yong Jiang, Nguyen Bach, et al.2021 · 206 citations
  19. InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and EfficiencyarXiv:2508.18265Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.2025 · 179 citations
  20. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
  21. GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation ModelsarXiv:2508.06471Aohan Zeng, Xin Lv, Qinkai Zheng, et al.2025 · 166 citations
  22. SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-trainingarXiv:2501.17161Tianzhe Chu, Yuexiang Zhai, Jihan Yang, et al.2025 · 160 citations
  23. SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the WildarXiv:2503.18892Weihao Zeng, Yuzhen Huang, Qian Liu, et al.2025 · 154 citations
  24. Process Reinforcement through Implicit RewardsarXiv:2502.01456Ganqu Cui, Lifan Yuan, Zefan Wang, et al.2025 · 151 citations
  25. rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep ThinkingarXiv:2501.04519Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al.2025 · 146 citations
  26. R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement LearningarXiv:2503.05592Huatong Song, Jinhao Jiang, Yingqian Min, et al.2025 · 141 citations
  27. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
  28. The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree SearcharXiv:2504.08066Yutaro Yamada, Robert Tjarko Lange, Cong Lu, et al.2025 · 129 citations
  29. L1: Controlling How Long A Reasoning Model Thinks With Reinforcement LearningarXiv:2503.04697Pranjal Aggarwal, Sean Welleck2025 · 125 citations
  30. Mem0: Building Production-Ready AI Agents with Scalable Long-Term MemoryarXiv:2504.19413Prateek Chhikara, Dev Khant, Saket Aryan, et al.2025 · 125 citations
  31. Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRsarXiv:2503.01307Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.2025 · 123 citations
  32. DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal DecompositionarXiv:2504.21801Z. Z. Ren, Zhihong Shao, Junxiao Song, et al.2025 · 122 citations
  33. The Alignment Problem from a Deep Learning PerspectivearXiv:2209.00626Richard Ngo, Lawrence Chan, Soren Mindermann2022 · 121 citations
  34. Agentless: Demystifying LLM-based Software Engineering AgentsarXiv:2407.01489Chunqiu Steven Xia, Yinlin Deng, Soren Dunn, et al.2024 · 117 citations
  35. UI-TARS: Pioneering Automated GUI Interaction with Native AgentsarXiv:2501.12326Yujia Qin, Yining Ye, Junjie Fang, et al.2025 · 112 citations
  36. Reasoning Models Don't Always Say What They ThinkarXiv:2505.05410Yanda Chen, Joe Benton, Ansh Radhakrishnan, et al.2025 · 106 citations
  37. TokenSkip: Controllable Chain-of-Thought Compression in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Heming Xia, Chak Tou Leong, Wenjie Wang, et al.2025 · 106 citations
  38. The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem ComplexityConference on Neural Information Processing Systems (NeurIPS)Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh, et al.2025 · 104 citations
  39. The Entropy Mechanism of Reinforcement Learning for Reasoning Language ModelsarXiv:2505.22617Ganqu Cui, Yuchen Zhang, Jiacheng Chen, et al.2025 · 101 citations
  40. MathArena: Evaluating LLMs on Uncontaminated Math CompetitionsConference on Neural Information Processing Systems (NeurIPS)Mislav Balunović, Jasper Dekoninck, Ivo Petrov, et al.2025 · 99 citations
  41. Chain of Draft: Thinking Faster by Writing LessarXiv:2502.18600Silei Xu, Wenhao Xie, Lingxiao Zhao, et al.2025 · 98 citations
  42. Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement LearningarXiv:2504.11354Haiming Wang, Mert Unsal, Xiaohan Lin, et al.2025 · 92 citations
  43. Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language ModelsarXiv:2503.06749Wenxuan Huang, Bohan Jia, Zijie Zhai, et al.2025 · 92 citations
  44. Dream 7B: Diffusion Large Language ModelsarXiv:2508.15487Jiacheng Ye; Zhihui Xie; Lin Zheng; Jiahui Gao; Zirui Wu; Xin Jiang; Zhenguo Li;, Lingpeng Kong2025 · 89 citations
  45. GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement LearningarXiv:2507.01006GLM-V Team, Wenyi Hong, Wenmeng Yu, et al.2025 · 89 citations
  46. SuperGPQA: Scaling LLM Evaluation across 285 Graduate DisciplinesarXiv:2502.14739M-A-P Team, Xinrun Du, Yifan Yao, et al.2025 · 89 citations
  47. ReTool: Reinforcement Learning for Strategic Tool Use in LLMsarXiv:2504.11536Jiazhan Feng, Shijue Huang, Xingwei Qu, et al.2025 · 88 citations
  48. HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMsarXiv:2412.18925Junying Chen, Zhenyang Cai, Ke Ji, et al.2024 · 87 citations
  49. 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
  50. A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?arXiv:2503.24235Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.2025 · 79 citations
  51. TTRL: Test-Time Reinforcement LearningConference on Neural Information Processing Systems (NeurIPS)Yuxin Zuo, Kaiyan Zhang, Li Sheng, et al.2025 · 76 citations
  52. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
  53. Training Language Models to Reason EfficientlyConference on Neural Information Processing Systems (NeurIPS)Daman Arora, Andrea Zanette2025 · 74 citations
  54. Rubrics as Rewards: Reinforcement Learning Beyond Verifiable DomainsarXiv:2507.17746Anisha Gunjal, Anthony Wang, Elaine Lau, et al.2025 · 73 citations
  55. WebThinker: Empowering Large Reasoning Models with Deep Research CapabilityConference on Neural Information Processing Systems (NeurIPS)Xiaoxi Li, Jiajie Jin, Guanting Dong, et al.2025 · 72 citations
  56. 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
  57. Competitive Programming with Large Reasoning ModelsarXiv:2502.06807OpenAI: Ahmed El-Kishky, Alexander Wei, Andre Saraiva, et al.2025 · 68 citations
  58. Learning to Reason under Off-Policy GuidanceConference on Neural Information Processing Systems (NeurIPS)Jianhao Yan, Yafu Li, Zican Hu, et al.2025 · 68 citations
  59. Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-CorrectionarXiv:2508.03613Yong Lin, Shange Tang, Bohan Lyu, et al.2025 · 67 citations
  60. Seed1.5-VL Technical ReportarXiv:2505.07062Dong Guo, Faming Wu, Feida Zhu, et al.2025 · 67 citations
  61. ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement LearningarXiv:2504.01296Bairu Hou, Yang Zhang, Jiabao Ji, et al.2025 · 67 citations
  62. Inference-Time Scaling for Generalist Reward ModelingarXiv:2504.02495Zijun Liu, Peiyi Wang, Runxin Xu, et al.2025 · 65 citations
  63. MedXpertQA: Benchmarking Expert-Level Medical Reasoning and UnderstandingarXiv:2501.18362Yuxin Zuo, Shang Qu, Yifei Li, et al.2025 · 65 citations
  64. CoT-Valve: Length-Compressible Chain-of-Thought TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Xinyin Ma, Guangnian Wan, Runpeng Yu, et al.2025 · 64 citations
  65. Phi-4-reasoning Technical ReportarXiv:2504.21318Marah Abdin, Sahaj Agarwal, Ahmed Awadallah, et al.2025 · 64 citations
  66. SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software EvolutionConference on Neural Information Processing Systems (NeurIPS)Yuxiang Wei, Olivier Duchenne, Jade Copet, et al.2025 · 64 citations
  67. Monitoring Reasoning Models for Misbehavior and the Risks of Promoting ObfuscationarXiv:2503.11926Bowen Baker, Joost Huizinga, Leo Gao, et al.2025 · 63 citations
  68. VinePPO: Refining Credit Assignment in RL Training of LLMsarXiv:2410.01679Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, et al.2024 · 63 citations
  69. Deep Think with ConfidencearXiv:2508.15260Yichao Fu, Xuewei Wang, Yuandong Tian, et al.2025 · 61 citations
  70. ZebraLogic: On the Scaling Limits of LLMs for Logical ReasoningarXiv:2502.01100Bill Yuchen Lin, Ronan Le Bras, Kyle Richardson, et al.2025 · 60 citations
  71. ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Mingjie Liu, Shizhe Diao, Ximing Lu, et al.2025 · 58 citations
  72. Absolute Zero: Reinforced Self-play Reasoning with Zero DataConference on Neural Information Processing Systems (NeurIPS)Andrew Zhao, Yiran Wu, Yang Yue, et al.2025 · 57 citations
  73. A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and BeyondarXiv:2503.21614Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.2025 · 55 citations
  74. PlanGenLLMs: A Modern Survey of LLM Planning CapabilitiesAnnual Meeting of the Association for Computational Linguistics (ACL)Hui Wei, Zihao Zhang, Shenghua He, et al.2025 · 55 citations
  75. MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning TasksConference of the European Chapter of the Association for Computational Linguistics (EACL)Lei Zhang, Yuge Zhang, Kan Ren, et al.2024 · 52 citations
  76. LightThinker: Thinking Step-by-Step CompressionConference on Empirical Methods in Natural Language Processing (EMNLP)Jintian Zhang, Yuqi Zhu, Mengshu Sun, et al.2025 · 50 citations
  77. ZeroSearch: Incentivize the Search Capability of LLMs without SearchingarXiv:2505.04588Hao Sun, Zile Qiao, Jiayan Guo, et al.2025 · 50 citations
  78. Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI SynergyarXiv:2507.01352Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.2025 · 48 citations
  79. Agentic Reasoning: A Streamlined Framework for Enhancing LLM Reasoning with Agentic ToolsAnnual Meeting of the Association for Computational Linguistics (ACL)Junde Wu, Jiayuan Zhu, Yuyuan Liu, et al.2025 · 45 citations
  80. General-Reasoner: Advancing LLM Reasoning Across All DomainsConference on Neural Information Processing Systems (NeurIPS)Xueguang Ma, Qian Liu, Dongfu Jiang, et al.2025 · 43 citations
  81. Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM ReasoningarXiv:2412.09078Zhenni Bi, Kai Han, Chuanjian Liu, et al.2024 · 43 citations
  82. SemEval-2026 Task 13: Detecting Machine-Generated Code with Multiple Programming Languages, Generators, and Application ScenariosInternational Workshop on Semantic Evaluation (SemEval)Daniil Orel, Dilshod Azizov, Indraneil Paul, et al.2026 · 41 citations
  83. DeepResearch Bench: A Comprehensive Benchmark for Deep Research AgentsarXiv:2506.11763Mingxuan Du, Benfeng Xu, Chiwei Zhu, et al.2025 · 41 citations
  84. Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?Annual Meeting of the Association for Computational Linguistics (ACL)Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.2025 · 38 citations
  85. Efficient Reasoning Models: A SurveyarXiv:2504.10903Sicheng Feng, Gongfan Fang, Xinyin Ma, et al.2025 · 37 citations
  86. SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language ModelsarXiv:2504.11468Hardy Chen, Haoqin Tu, Fali Wang, et al.2025 · 37 citations
  87. SciKnowEval: Evaluating Multi-level Scientific Knowledge of Large Language ModelsarXiv:2406.09098Kehua Feng, Xinyi Shen, Weijie Wang, et al.2024 · 36 citations
  88. People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated textAnnual Meeting of the Association for Computational Linguistics (ACL)Jenna Russell, Marzena Karpinska, Mohit Iyyer2025 · 33 citations
  89. The Hidden Risks of Large Reasoning Models: A Safety Assessment of R1International Joint Conference on Natural Language Processing (IJCNLP)Kaiwen Zhou, Chengzhi Liu, Xuandong Zhao, et al.2025 · 30 citations
  90. Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the AboveAnnual Meeting of the Association for Computational Linguistics (ACL)Nishant Balepur, Rachel Rudinger, Jordan Boyd-Graber2025 · 28 citations
  91. S²R: Teaching LLMs to Self-verify and Self-correct via Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Ruotian Ma, Peisong Wang, Cheng Liu, et al.2025 · 26 citations
  92. UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement LearningarXiv:2509.02544Haoming Wang, Haoyang Zou, Huatong Song, et al.2025 · 26 citations
  93. Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Haoxiang Sun, Yingqian Min, Zhipeng Chen, et al.2026 · 25 citations
  94. Audio-Reasoner: Improving Reasoning Capability in Large Audio Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Xie Zhifei, Mingbao Lin, Zihang Liu, et al.2025 · 25 citations
  95. The State of Multilingual LLM Safety Research: From Measuring The Language Gap To Mitigating ItConference on Empirical Methods in Natural Language Processing (EMNLP)Zheng Xin Yong, Beyza Ermis, Marzieh Fadaee, et al.2025 · 25 citations
  96. Linguistic Generalizability of Test-Time Scaling in Mathematical ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Guijin Son, Jiwoo Hong, Hyunwoo Ko, et al.2025 · 24 citations
  97. Personalized Generation In Large Model Era: A SurveyAnnual Meeting of the Association for Computational Linguistics (ACL)Yiyan Xu, Jinghao Zhang, Alireza Salemi, et al.2025 · 24 citations
  98. Chain-of-Reasoning: Towards Unified Mathematical Reasoning in Large Language Models via a Multi-Paradigm PerspectiveAnnual Meeting of the Association for Computational Linguistics (ACL)Yiyao Yu, Yuxiang Zhang, Dongdong Zhang, et al.2025 · 23 citations
  99. VRAG-RL: Empower Vision-Perception-Based RAG for Visually Rich Information Understanding via Iterative Reasoning with Reinforcement LearningConference on Neural Information Processing Systems (NeurIPS)Qiuchen Wang, Ruixue Ding, Yu Zeng, et al.2025 · 23 citations
  100. Online Difficulty Filtering for Reasoning Oriented Reinforcement LearningConference of the European Chapter of the Association for Computational Linguistics (EACL)Sanghwan Bae, Jiwoo Hong, Min Young Lee, et al.2026 · 22 citations

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