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Who cites Feryal Behbahani

300 citations of their works from 294 papers of our library (of the 149,439 whose bibliographies we read) · 101 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Feryal Behbahani

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  1. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement LearningNatureDeepSeek-AI, Daya Guo, Dejian Yang, et al.2025 · 4,728 citations
  2. 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
  3. A Survey on In-context LearningarXiv:2301.00234Qingxiu Dong, Lei Li, Damai Dai, et al.2023 · 978 citations
  4. Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingarXiv:2411.15124Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024 · 423 citations
  5. 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
  6. 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
  7. Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMsarXiv:2412.21187Xingyu Chen, Jiahao Xu, Tian Liang, et al.2024 · 192 citations
  8. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesarXiv:2406.06608Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 189 citations
  9. 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
  10. BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex InstructionsarXiv:2406.15877Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.2024 · 176 citations
  11. Generative Verifiers: Reward Modeling as Next-Token PredictionarXiv:2408.15240Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.2024 · 152 citations
  12. Beyond Human Data: Scaling Self-Training for Problem-Solving with Language ModelsarXiv:2312.06585Avi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.2023 · 147 citations
  13. 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
  14. LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context MultitasksarXiv:2412.15204Yushi Bai, Shangqing Tu, Jiajie Zhang, et al.2024 · 135 citations
  15. 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
  16. Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language ModelsarXiv:2501.09686Fengli Xu, Qianyue Hao, Zefang Zong, et al.2025 · 120 citations
  17. BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-HaystackConference on Neural Information Processing Systems (NeurIPS)Yuri Kuratov, Aydar Bulatov, Petr Anokhin, et al.2024 · 88 citations
  18. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
  19. HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMsarXiv:2412.18925Junying Chen, Zhenyang Cai, Ke Ji, et al.2024 · 87 citations
  20. In-Context Learning with Long-Context Models: An In-Depth ExplorationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Amanda Bertsch, Maor Ivgi, Emily Xiao, et al.2025 · 81 citations
  21. Training Language Models to Reason EfficientlyConference on Neural Information Processing Systems (NeurIPS)Daman Arora, Andrea Zanette2025 · 74 citations
  22. RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement LearningarXiv:2504.20073Zihan Wang, Kangrui Wang, Qineng Wang, et al.2025 · 71 citations
  23. 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
  24. 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
  25. HELMET: How to Evaluate Long-Context Language Models Effectively and ThoroughlyarXiv:2410.02694Howard Yen, Tianyu Gao, Minmin Hou, et al.2024 · 55 citations
  26. Evaluating the Capabilities of Large Language Models for Multi-label Emotion UnderstandingInternational Conference on Computational Linguistics (COLING)Tadesse Destaw Belay, Israel Abebe Azime, Abinew Ali Ayele, et al.2025 · 52 citations
  27. From Decoding to Meta-Generation: Inference-time Algorithms for Large Language ModelsarXiv:2406.16838Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.2024 · 51 citations
  28. RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement LearningarXiv:2410.02089Jonas Gehring, Kunhao Zheng, Jade Copet, et al.2024 · 51 citations
  29. MiniMax-01: Scaling Foundation Models with Lightning AttentionarXiv:2501.08313MiniMax, Aonian Li, Bangwei Gong, et al.2025 · 50 citations
  30. Darwin Godel Machine: Open-Ended Evolution of Self-Improving AgentsarXiv:2505.22954Jenny Zhang, Shengran Hu, Cong Lu, et al.2025 · 47 citations
  31. DeepSeek-R1 Thoughtology: Let's think about LLM ReasoningarXiv:2504.07128Sara Vera Marjanovic, Arkil Patel, Vaibhav Adlakha, et al.2025 · 47 citations
  32. Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-ThoughtarXiv:2501.04682Violet Xiang, Charlie Snell, Kanishk Gandhi, et al.2025 · 47 citations
  33. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations
  34. 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
  35. A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic SystemsarXiv:2504.09037Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.2025 · 39 citations
  36. Agentic Context Engineering: Evolving Contexts for Self-Improving Language ModelsarXiv:2510.04618Qizheng Zhang, Changran Hu, Shubhangi Upasani, et al.2025 · 39 citations
  37. ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning AgentsConference on Empirical Methods in Natural Language Processing (EMNLP)Qiuchen Wang, Ruixue Ding, Zehui Chen, et al.2025 · 39 citations
  38. 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
  39. Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn'tarXiv:2503.16219Quy-Anh Dang, Chris Ngo2025 · 37 citations
  40. A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super IntelligencearXiv:2507.21046Huan-ang Gao, Jiayi Geng, Wenyue Hua, et al.2025 · 36 citations
  41. Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure QueriesarXiv:2409.12640Kiran Vodrahalli; Santiago Ontanon; Nilesh Tripuraneni; Kelvin Xu; Sanil Jain; Rakesh Shivanna; Jeffrey Hui; Nishanth Dikkala; Mehran Kazemi; Bahare Fatemi; Rohan Anil; Ethan Dyer; Siamak Shakeri; Roopali Vij; Harsh Mehta; Vinay Ramasesh; Quoc Le; Ed Chi; Yifeng Lu; Orhan Firat; Angeliki Lazaridou; Jean-Baptiste Lespiau; Nithya Attaluri;, Kate Olszewska2024 · 35 citations
  42. CLIN: A Continually Learning Language Agent for Rapid Task Adaptation and GeneralizationarXiv:2310.10134Bodhisattwa Prasad Majumder, Bhavana Dalvi Mishra, Peter Jansen, et al.2023 · 34 citations
  43. Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning PerspectivearXiv:2412.14135Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.2024 · 33 citations
  44. T1: Advancing Language Model Reasoning through Reinforcement Learning and Inference ScalingarXiv:2501.11651Zhenyu Hou, Xin Lv, Rui Lu, et al.2025 · 28 citations
  45. Scaling Test-Time Compute Without Verification or RL is SuboptimalarXiv:2502.12118Amrith Setlur, Nived Rajaraman, Sergey Levine, et al.2025 · 26 citations
  46. 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
  47. How Is LLM Reasoning Distracted by Irrelevant Context? An Analysis Using a Controlled BenchmarkMinglai Yang, Ethan Huang, Liang Zhang, et al.2025 · 25 citations
  48. 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
  49. Self-Evolving Curriculum for LLM ReasoningarXiv:2505.14970Xiaoyin Chen, Jiarui Lu, Minsu Kim, et al.2025 · 20 citations
  50. MindSearch: Mimicking Human Minds Elicits Deep AI SearcherarXiv:2407.20183Zehui Chen, Kuikun Liu, Qiuchen Wang, et al.2024 · 20 citations
  51. A Survey of Post-Training Scaling in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Hanyu Lai, Xiao Liu, Junjie Gao, et al.2025 · 18 citations
  52. Hunyuan-MT Technical ReportarXiv:2509.05209Mao Zheng, Zheng Li, Bingxin Qu, et al.2025 · 17 citations
  53. Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language ModelsarXiv:2412.02980Alex Havrilla, Andrew Dai, Laura O'Mahony, et al.2024 · 17 citations
  54. Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language ModelsarXiv:2503.24377Rui Wang, Hongru Wang, Boyang Xue, et al.2025 · 16 citations
  55. MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Chanwoo Park, Seungju Han, Xingzhi Guo, et al.2025 · 15 citations
  56. From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical DebuggingIEEE/ACM International Conference on Software Engineering (ICSE)Yuling Shi, Songsong Wang, Chengcheng Wan, et al.2024 · 15 citations
  57. OMNI-EPIC: Open-endedness via Models of human Notions of Interestingness with Environments Programmed in CodearXiv:2405.15568Maxence Faldor, Jenny Zhang, Antoine Cully, et al.2024 · 15 citations
  58. Mastering Board Games by External and Internal Planning with Language ModelsarXiv:2412.12119John Schultz, Jakub Adamek, Matej Jusup, et al.2024 · 14 citations
  59. POSITION BIAS MITIGATES POSITION BIAS: Mitigate Position Bias Through Inter-Position Knowledge DistillationConference on Empirical Methods in Natural Language Processing (EMNLP)Yifei Wang, Feng Xiong, Yong Wang, et al.2025 · 13 citations
  60. Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive SearcharXiv:2502.02508Maohao Shen, Guangtao Zeng, Zhenting Qi, et al.2025 · 13 citations
  61. Confidence v.s. Critique: A Decomposition of Self-Correction Capability for LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhe Yang, Yichang Zhang, Yudong Wang, et al.2025 · 11 citations
  62. Augmenting Autotelic Agents with Large Language ModelsarXiv:2305.12487Cedric Colas, Laetitia Teodorescu, Pierre-Yves Oudeyer, et al.2023 · 11 citations
  63. Can Many-Shot In-Context Learning Help LLMs as Evaluators? A Preliminary Empirical StudyInternational Conference on Computational Linguistics (COLING)Mingyang Song, Mao Zheng, Xuan Luo2025 · 9 citations
  64. TESS 2: A Large-Scale Generalist Diffusion Language ModelAnnual Meeting of the Association for Computational Linguistics (ACL)Jaesung Tae, Hamish Ivison, Sachin Kumar, et al.2025 · 9 citations
  65. Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier EngineeringarXiv:2411.11504Xinyan Guan, Yanjiang Liu, Xinyu Lu, et al.2024 · 9 citations
  66. On Many-Shot In-Context Learning for Long-Context EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Kaijian Zou, Muhammad Khalifa, Lu Wang2025 · 8 citations
  67. PAG: Multi-Turn Reinforced LLM Self-Correction with Policy as Generative VerifierarXiv:2506.10406Yuhua Jiang, Yuwen Xiong, Yufeng Yuan, et al.2025 · 8 citations
  68. R-Search: Empowering LLM Reasoning with Search via Multi-Reward Reinforcement LearningFindings of the Association for Computational LinguisticsQingfei Zhao, Ruobing Wang, Dingling Xu, et al.2026 · 7 citations
  69. Math Neurosurgery: Isolating Language Models' Math Reasoning Abilities Using Only Forward PassesAnnual Meeting of the Association for Computational Linguistics (ACL)Bryan R Christ, Zachary Gottesman, Jonathan Kropko, et al.2025 · 7 citations
  70. CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving ChallengesFindings of the Association for Computational LinguisticsZihan Wang, Lam Nguyen, Zhengyang Zhao, et al.2026 · 6 citations
  71. Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and DistillationarXiv:2502.01694Juno Kim, Denny Wu, Jason Lee, et al.2025 · 6 citations
  72. MAVEN-FACT: A Large-scale Event Factuality Detection DatasetFindings of the Association for Computational LinguisticsChunyang Li, Hao Peng, Xiaozhi Wang, et al.2024 · 6 citations
  73. Don't Act Blindly: Robust GUI Automation via Action-Effect Verification and Self-CorrectionAnnual Meeting of the Association for Computational Linguistics (ACL)Yuzhe Zhang, Xianwei Xue, Xingyong Wu, et al.2026 · 5 citations
  74. Language-Coupled Reinforcement Learning for Multilingual Retrieval-Augmented GenerationFindings of the Association for Computational LinguisticsRui Qi, Fengran Mo, Yufeng Chen, et al.2026 · 5 citations
  75. Beyond Many-Shot Translation: Scaling In-Context Demonstrations For Low-Resource Machine TranslationWorkshop on Language Models for Low-Resource LanguagesLuis Frentzen Salim, Esteban Carlin, Alexandre Morinvil, et al.2026 · 2 citations
  76. From Belief Entrenchment to Robust Reasoning in LLM AgentsTransactions of the Association for Computational Linguistics (TACL)Jihwan Oh, Minchan Jeong, Jongwoo Ko, et al.2026 · 2 citations
  77. Training AI Scientists to Replicate ResearcharXiv:2608.13331Damon Falck, Samer Sabri, Anja Surina, et al.2026 · 2 citations
  78. Reading the unreadable: Creating a dataset of 19th century English newspapers using image-to-text language modelsarXiv:2502.14901Jonathan Bourne2025 · 2 citations
  79. Correct, Concise and Complete: Multi-stage Training For Adaptive ReasoningFindings of the Association for Computational LinguisticsNathanaël Carraz Rakotonirina, Ren Pang, Neha Anna John, et al.2026 · 1 citation
  80. Meeseeks: A Feedback-Driven, Iterative Self-Correction Benchmark evaluating LLMs' Instruction Following CapabilityFindings of the Association for Computational LinguisticsJiaming Wang, Yunke Zhao, Peng Ding, et al.2026 · 1 citation
  81. On Safety Risks in Experience-Driven Self-Evolving AgentsFindings of the Association for Computational LinguisticsWeixiang Zhao, Yichen Zhang, Yingshuo Wang, et al.2026 · 1 citation
  82. Reasoning or Knowledge: Stratified Evaluation of Biomedical LLMsConference of the European Chapter of the Association for Computational Linguistics (EACL)Rahul Thapa, Qingyang Wu, Kevin Wu, et al.2026 · 1 citation
  83. Robust Tool Use via Fission-GRPO: Learning to Recover from Execution ErrorsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiwei Zhang, Fei Zhao, Rui Wang, et al.2026 · 1 citation
  84. A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and SolutionsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.2026
  85. AdapShot: Adaptive Many-Shot In-Context Learning with Semantic-Aware KV Cache ReuseAnnual Meeting of the Association for Computational Linguistics (ACL)Jie Ou, Jinyu Guo, Shiyao Guo, et al.2026
  86. Adaptive Test-Time Compute Allocation with Evolving In-Context DemonstrationsFindings of the Association for Computational LinguisticsBowen Zuo, Dongruo Zhou, Yinglun Zhu2026
  87. Beyond Memorization: Extending Reasoning Depth with Recurrence, Memory and Test-Time Compute ScalingFindings of the Association for Computational LinguisticsIvan Rodkin, Daniil Orel, Konstantin Smirnov, et al.2026
  88. Can LLMs Self-Correct Table Reasoning Errors?Workshop on Structured Understanding, Retrieval, and Generation in the LLM EraFarseen Shaikh2026
  89. CheckRLM: Effective Knowledge–Thought Coherence Checking in Retrieval-Augmented ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Dingling Xu, Ruobing Wang, Qingfei Zhao, et al.2026
  90. Deliberative Searcher: Improving LLM Reliability via Reinforcement Learning with ConstraintsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhenyun Yin, Shujie Wang, Xuhong Wang, et al.2026
  91. Distilling Examples into Task Instructions: Enhanced In-Context Learning for Real-World B2B ConversationsFindings of the Association for Computational LinguisticsGuy Rotman, Adi Kopilov, Danit Berger Zalmanson, et al.2026
  92. EvoMD-LLM: Learning the Language of Species Evolution in Reactive Molecular DynamicsFindings of the Association for Computational LinguisticsZhichen Tang, Zhengzheng Dang, Yulin Chen, et al.2026
  93. Generalizable LLM Learning of Graph Synthetic Data with Post-training AlignmentFindings of the Association for Computational LinguisticsYizhuo Zhang, Heng Wang, Shangbin Feng, et al.2026
  94. Generative Information Extraction from Biographical SourcesWorkshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL)Robin Winkle, Manfred Stede, Jörn Kreutel2026
  95. LoVeC: Reinforcement Learning for Better Verbalized Confidence in Long-Form GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Caiqi Zhang, Xiaochen Zhu, Chengzu Li, et al.2026
  96. PaT: Planning-after-Trial for Efficient Test-Time Code GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Youngsik Yoon, Sungjae Lee, Seockbean Song, et al.2026
  97. Scaling Performance and Low-Resource Annotation with Many-Shot In-Context Learning for Named Entity RecognitionFindings of the Association for Computational LinguisticsQi Zhang, Fangping Lan, Cornelia Caragea, et al.2026
  98. Self-Reflective Generation at Test TimeAnnual Meeting of the Association for Computational Linguistics (ACL)Jian Mu, Qixin Zhang, Zhiyong Wang, et al.2026
  99. Soft Head Selection for Injecting ICL-Derived Task EmbeddingsFindings of the Association for Computational LinguisticsJungwon Park, Jimyeong Kim, Changin Choi, et al.2026
  100. ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Vladislav Smirnov, Quang-Chieu Nguyen, Sergey Senichev, et al.2026

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