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Who cites Michal Valko

581 citations of their works from 560 papers of our library (of the 149,439 whose bibliographies we read) · 104 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Michal Valko

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  1. Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020Alec Radford, Jong Wook Kim, Chris Hallacy, et al.2021 · 8,767 citations
  2. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
  3. Emerging Properties in Self-Supervised Vision TransformersIEEE/CVF International Conference on Computer Vision (ICCV)Mathilde Caron, Hugo Touvron, Ishan Misra, et al.2021 · 6,046 citations
  4. HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden UnitsIEEE/ACM Transactions on Audio Speech and Language ProcessingWei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, et al.2021 · 3,458 citations
  5. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
  6. Scaling Up Visual and Vision-Language Representation Learning With Noisy Text SupervisionInternational Conference on Machine Learning (ICML)Chao Jia, Yinfei Yang, Ye Xia, et al.2021 · 1,615 citations
  7. DINOv2: Learning Robust Visual Features without SupervisionarXiv:2304.07193Maxime Oquab, Timothee Darcet, Theo Moutakanni, et al.2023 · 1,513 citations
  8. Masked Autoencoders Are Scalable Vision LearnersarXiv:2111.06377Kaiming He, Xinlei Chen, Saining Xie, et al.2021 · 596 citations
  9. CogView: Mastering Text-to-Image Generation via TransformersarXiv:2105.13290Ming Ding, Zhuoyi Yang, Wenyi Hong, et al.2021 · 469 citations
  10. OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning FrameworkarXiv:2202.03052Peng Wang, An Yang, Rui Men, et al.2022 · 467 citations
  11. DiffCSE: Difference-based Contrastive Learning for Sentence EmbeddingsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Yung-Sung Chuang, Rumen Dangovski, Hongyin Luo, et al.2022 · 269 citations
  12. Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-ExpertsFindings of the Association for Computational LinguisticsHaoxiang Wang, Wei Xiong, Tengyang Xie, et al.2024 · 153 citations
  13. Process Reinforcement through Implicit RewardsarXiv:2502.01456Ganqu Cui, Lifan Yuan, Zefan Wang, et al.2025 · 151 citations
  14. Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with NothingarXiv:2406.08464Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.2024 · 148 citations
  15. InternVideo: General Video Foundation Models via Generative and Discriminative LearningarXiv:2212.03191Yi Wang, Kunchang Li, Yizhuo Li, et al.2022 · 144 citations
  16. ReFT: Reasoning with Reinforced Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Luong Trung, Xinbo Zhang, Zhanming Jie, et al.2024 · 134 citations
  17. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
  18. Fanar: An Arabic-Centric Multimodal Generative AI PlatformarXiv:2501.13944Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.2025 · 127 citations
  19. SaulLM-7B: A pioneering Large Language Model for LawarXiv:2403.03883Pierre Colombo, Telmo Pessoa Pires, Malik Boudiaf, et al.2024 · 119 citations
  20. ALLaM: Large Language Models for Arabic and EnglisharXiv:2407.15390M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.2024 · 113 citations
  21. Orca-Math: Unlocking the potential of SLMs in Grade School MatharXiv:2402.14830Arindam Mitra, Hamed Khanpour, Corby Rosset, et al.2024 · 111 citations
  22. RLHF Workflow: From Reward Modeling to Online RLHFarXiv:2405.07863Hanze Dong, Wei Xiong, Bo Pang, et al.2024 · 111 citations
  23. Nemotron-4 340B Technical ReportarXiv:2406.11704Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.2024 · 107 citations
  24. Multi-Step Reasoning with Large Language Models, a SurveyACM Computing SurveysAske Plaat, Annie Wong, Suzan Verberne, et al.2024 · 106 citations
  25. AnglE-optimized Text EmbeddingsarXiv:2309.12871Xianming Li, Jing Li2023 · 103 citations
  26. Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-ConstraintarXiv:2312.11456Wei Xiong, Hanze Dong, Chenlu Ye, et al.2023 · 100 citations
  27. A Survey of Reinforcement Learning from Human FeedbackTransactions on Machine Learning ResearchTimo Kaufmann, Paul Weng, Viktor Bengs, et al.2023 · 92 citations
  28. Mitigating the Alignment Tax of RLHFConference on Empirical Methods in Natural Language Processing (EMNLP)Yong Lin, Hangyu Lin, Wei Xiong, et al.2024 · 83 citations
  29. Smaug: Fixing Failure Modes of Preference Optimisation with DPO-PositivearXiv:2402.13228Arka Pal, Deep Karkhanis, Samuel Dooley, et al.2024 · 82 citations
  30. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
  31. From r to Q*: Your Language Model is Secretly a Q-FunctionarXiv:2404.12358Rafael Rafailov, Joey Hejna, Ryan Park, et al.2024 · 72 citations
  32. Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Haoxiang Wang, Yong Lin, Wei Xiong, et al.2024 · 68 citations
  33. Towards Understanding Grokking: An Effective Theory of Representation LearningConference on Neural Information Processing Systems (NeurIPS)Ziming Liu, Ouail Kitouni, Niklas Nolte, et al.2022 · 65 citations
  34. The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-DeterminismConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Yifan Song, Guoyin Wang, Sujian Li, et al.2025 · 64 citations
  35. Free Process Rewards without Process LabelsarXiv:2412.01981Lifan Yuan, Wendi Li, Huayu Chen, et al.2024 · 58 citations
  36. Generative Reward ModelsarXiv:2410.12832Dakota Mahan, Duy Van Phung, Rafael Rafailov, et al.2024 · 58 citations
  37. RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-FoldConference on Neural Information Processing Systems (NeurIPS)Amrith Setlur, Saurabh Garg, Xinyang Geng, et al.2024 · 56 citations
  38. Pedagogical Alignment of Large Language ModelsFindings of the Association for Computational Linguistics: EMNLP 2024Shashank Sonkar, Kangqi Ni, Sapana Chaudhary, et al.2024 · 54 citations
  39. Critique-out-Loud Reward ModelsarXiv:2408.11791Zachary Ankner, Mansheej Paul, Brandon Cui, et al.2024 · 52 citations
  40. Easy-to-Hard Generalization: Scalable Alignment Beyond Human SupervisionConference on Neural Information Processing Systems (NeurIPS)Zhiqing Sun, Longhui Yu, Yikang Shen, et al.2024 · 51 citations
  41. mDPO: Conditional Preference Optimization for Multimodal Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Fei Wang, Wenxuan Zhou, James Y. Huang, et al.2024 · 50 citations
  42. Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference FeedbackConference on Neural Information Processing Systems (NeurIPS)Hamish Ivison, Yizhong Wang, Jiacheng Liu, et al.2024 · 50 citations
  43. Direct Nash Optimization: Teaching Language Models to Self-Improve with General PreferencesarXiv:2404.03715Corby Rosset, Ching-An Cheng, Arindam Mitra, et al.2024 · 44 citations
  44. Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference OptimizationarXiv:2411.10442Weiyun Wang, Zhe Chen, Wenhai Wang, et al.2024 · 44 citations
  45. AI-Researcher: Autonomous Scientific InnovationConference on Neural Information Processing Systems (NeurIPS)Jiabin Tang, Lianghao Xia, Zhonghang Li, et al.2025 · 40 citations
  46. 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
  47. ODIN: Disentangled Reward Mitigates Hacking in RLHFarXiv:2402.07319Lichang Chen, Chen Zhu, Davit Soselia, et al.2024 · 38 citations
  48. Data Distillation: A SurveyarXiv:2301.04272Noveen Sachdeva, Julian McAuley2023 · 37 citations
  49. Self-Refine Instruction-Tuning for Aligning Reasoning in Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Leonardo Ranaldi, Andre Freitas2024 · 35 citations
  50. Nash Learning from Human FeedbackarXiv:2312.00886Remi Munos, Michal Valko, Daniele Calandriello, et al.2023 · 32 citations
  51. LiPO: Listwise Preference Optimization through Learning-to-RankConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Tianqi Liu, Zhen Qin, Junru Wu, et al.2025 · 31 citations
  52. Learning Planning-based Reasoning by Trajectories Collection and Process Reward SynthesizingConference on Empirical Methods in Natural Language Processing (EMNLP)Fangkai Jiao, Chengwei Qin, Zhengyuan Liu, et al.2024 · 31 citations
  53. LLM-as-a-Judge & Reward Model: What They Can and Cannot DoarXiv:2409.11239Guijin Son, Hyunwoo Ko, Hoyoung Lee, et al.2024 · 27 citations
  54. Binary Classifier Optimization for Large Language Model AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Seungjae Jung, Gunsoo Han, Daniel Wontae Nam, et al.2025 · 26 citations
  55. NaturalReasoning: Reasoning in the Wild with 2.8M Challenging QuestionsConference on Neural Information Processing Systems (NeurIPS)Weizhe Yuan, Jane Yu, Song Jiang, et al.2025 · 26 citations
  56. BOND: Aligning LLMs with Best-of-N DistillationarXiv:2407.14622Pier Giuseppe Sessa, Robert Dadashi, Leonard Hussenot, et al.2024 · 23 citations
  57. Step-Controlled DPO: Leveraging Stepwise Error for Enhanced Mathematical ReasoningarXiv:2407.00782Zimu Lu, Aojun Zhou, Ke Wang, et al.2024 · 23 citations
  58. Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-GenerationarXiv:2410.02725Rohin Manvi, Anikait Singh, Stefano Ermon2024 · 22 citations
  59. Personality Alignment of Large Language ModelsarXiv:2408.11779Minjun Zhu, Yixuan Weng, Linyi Yang, et al.2024 · 21 citations
  60. Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in AlignmentTransactions of the Association for Computational Linguistics (TACL)Karel D'Oosterlinck, Winnie Xu, Chris Develder, et al.2025 · 20 citations
  61. UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language ModelsarXiv:2502.00334Xin Xu, Qiyun Xu, Tong Xiao, et al.2025 · 19 citations
  62. Weak-to-Strong Search: Align Large Language Models via Searching over Small Language ModelsConference on Neural Information Processing Systems (NeurIPS)Zhanhui Zhou, Zhixuan Liu, Jie Liu, et al.2024 · 17 citations
  63. Self-Supervised Alignment with Mutual Information: Learning to Follow Principles without Preference LabelsConference on Neural Information Processing Systems (NeurIPS)Jan-Philipp Franken, Eric Zelikman, Rafael Rafailov, et al.2024 · 16 citations
  64. Outcome-based Exploration for LLM ReasoningarXiv:2509.06941Yuda Song, Julia Kempe, Remi Munos2025 · 15 citations
  65. MTSA: Multi-turn Safety Alignment for LLMs through Multi-round Red-teamingAnnual Meeting of the Association for Computational Linguistics (ACL)Weiyang Guo, Jing Li, Wenya Wang, et al.2025 · 14 citations
  66. Discovering Preference Optimization Algorithms with and for Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Chris Lu, Samuel Holt, Claudio Fanconi, et al.2024 · 14 citations
  67. The N+ Implementation Details of RLHF with PPO: A Case Study on TL;DR SummarizationarXiv:2403.17031Shengyi Huang, Michael Noukhovitch, Arian Hosseini, et al.2024 · 14 citations
  68. Meta-Reasoner: Dynamic Guidance for Optimized Inference-time Reasoning in Large Language ModelsFindings of the Association for Computational LinguisticsYuan Sui, Yufei He, Tri Cao, et al.2026 · 13 citations
  69. SaRO: Enhancing LLM Safety through Reasoning-based AlignmentarXiv:2504.09420Yutao Mou, Yuxiao Luo, Shikun Zhang, et al.2025 · 11 citations
  70. Nemotron-CrossThink: Scaling Self-Learning beyond Math ReasoningConference of the European Chapter of the Association for Computational Linguistics (EACL)Syeda Nahida Akter, Shrimai Prabhumoye, Matvei Novikov, et al.2026 · 9 citations
  71. 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
  72. Genius: A Generalizable and Purely Unsupervised Self-Training Framework For Advanced ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Fangzhi Xu, Hang Yan, Chang Ma, et al.2025 · 8 citations
  73. Selective Preference Optimization via Token-Level Reward Function EstimationConference on Empirical Methods in Natural Language Processing (EMNLP)Kailai Yang, Zhiwei Liu, Qianqian Xie, et al.2025 · 8 citations
  74. MPO: Multilingual Safety Alignment via Reward Gap OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Weixiang Zhao, Yulin Hu, Yang Deng, et al.2025 · 7 citations
  75. MetaFaith: Faithful Natural Language Uncertainty Expression in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Gabrielle Kaili-May Liu, Gal Yona, Avi Caciularu, et al.2025 · 6 citations
  76. FanarGuard: A Culturally-Aware Moderation Filter for Arabic Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Masoomali Fatehkia, Enes Altinisik, Husrev Taha Sencar2026 · 5 citations
  77. GAM: Hierarchical Graph-based Agentic Memory for LLM AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhaofen Wu, Hanrong Zhang, Fulin Lin, et al.2026 · 5 citations
  78. MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive TrainingAnnual Meeting of the Association for Computational Linguistics (ACL)Hui Huang, Jiaheng Liu, Yancheng He, et al.2025 · 4 citations
  79. MedQA-CS: Objective Structured Clinical Examination (OSCE)-Style Benchmark for Evaluating LLM Clinical SkillsConference of the European Chapter of the Association for Computational Linguistics (EACL)Zonghai Yao, Zihao Zhang, Chaolong Tang, et al.2026 · 3 citations
  80. Bias Fitting to Mitigate Length Bias of Reward Model in RLHFAnnual Meeting of the Association for Computational Linguistics (ACL)Kangwen Zhao, Jianfeng Cai, Jinhua Zhu, et al.2026 · 2 citations
  81. Gained in Translation: Privileged Pairwise Judges Enhance Multilingual ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Lintang Sutawika, Gokul Swamy, Steven Wu, et al.2026 · 2 citations
  82. Beyond Compromise: Pareto-Lenient Consensus for Efficient Multi-Preference LLM AlignmentFindings of the Association for Computational LinguisticsRenxuan Tan, Rongpeng Li, Zhifeng Zhao, et al.2026 · 1 citation
  83. CoAct: Co-Active LLM Preference Learning with Human-AI SynergyAnnual Meeting of the Association for Computational Linguistics (ACL)Ruiyao Xu, Mihir Parmar, Tiankai Yang, et al.2026 · 1 citation
  84. Energy Matching based Preference Learning for Diffusion Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Shiv Shankar2026 · 1 citation
  85. MEAV: Model Editing with Alignment Vectors for inference time LLM alignment in single and multidomain preference spectrumFindings of the Association for Computational LinguisticsSadat Shahriar, Zheng Qi, Nikolaos Pappas, et al.2026 · 1 citation
  86. What Makes LLMs Effective Sequential Recommenders? A Study on Preference Intensity and Temporal ContextAnnual Meeting of the Association for Computational Linguistics (ACL)Zhongyu Ouyang, Qianlong Wen, Chunhui Zhang, et al.2026 · 1 citation
  87. Safe at the Margins: A General Approach to Safety Alignment in Low-Resource English Languages — A Singlish Case StudyarXiv:2502.12485Isaac Lim, Shaun Khoo, Roy Ka-Wei Lee, et al.2025 · 1 citation
  88. Alignment Tuning for Large Language Models: A Data-Centric Lens on Alignment Data PipelinesFindings of the Association for Computational LinguisticsHwanjun Song2026
  89. BiasGRPO: Stabilizing Bias Mitigation in High-Variance Reward Landscapes via Group-Relative Policy OptimizationFindings of the Association for Computational LinguisticsSaket Reddy, Ke Yang, ChengXiang Zhai2026
  90. Context-Value-Action Architecture for Value-Driven Large Language Model AgentsFindings of the Association for Computational LinguisticsTianZe Zhang, Sirui Sun, Yuhang Xie, et al.2026
  91. DynamicFocalPO: Adaptive Focusing Strategy for Preference OptimizationFindings of the Association for Computational LinguisticsShu Zhou, Junan Chen, Rui Ling, et al.2026
  92. Experience is the Teacher: Reusing Atomic Thoughts from LLMs to Improve Medical DialogueFindings of the Association for Computational LinguisticsGuangya Yu, Hui Luo, Qi Ye, et al.2026
  93. FLAIR: Steering LLM Mathematical Problem Solving based on A Fuzzy-Logic-AssIsted ReasonerAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Wu, Hongru Sun, Wanqing Li, et al.2026
  94. Flout at Your Own Risk: LLMs Struggle with Pragmatic Cooperativity Under Epistemic AsymmetryarXiv:2607.11053Hannah VanderHoeven, Abhijnan Nath, Nikhil Krishnaswamy2026
  95. From Explicit to Implicit: A Theoretical Framework and Transfer Method for Preference Internalization in Language ModelsTransactions of the Association for Computational Linguistics (TACL)Binrui Wang, Yongping Du, Yu Pei, et al.2026
  96. Joint Optimization of Training Data and Policy in RLHFFindings of the Association for Computational LinguisticsZhuohao Yu, Jiali Zeng, Weizheng Gu, et al.2026
  97. Leveraging Unannotated Sign Language Data via a Robust Data Augmentation Method for Contrastive Representation LearningLREC Workshop on the Representation and Processing of Sign Languages: Language in MotionAriel Basso Madjoukeng, Pierre Poitier, Belise Edith Kenmogne, et al.2026
  98. Mitigating Cultural Bias in LLMs via Multi-Agent Cultural DebateFindings of the Association for Computational LinguisticsQian Tan, Lei Jiang, Yuting Zeng, et al.2026
  99. Pseudo-Likelihood Training for Reasoning Diffusion Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Shiv Shankar2026
  100. Revisiting Self-Play Preference Optimization: On the Role of Prompt DifficultyFindings of the Association for Computational LinguisticsYao Xiao, Jung-jae Kim, Roy Ka-Wei Lee, et al.2026

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