🧑‍🔬 Who cites Sham M. Kakade

335 citations of their works from 328 papers of our library (of the 149,439 whose bibliographies we read) · 97 with a page here, the most cited first · ← Sham M. Kakade

1. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
2. DeCAF: A Deep Convolutional Activation Feature for Generic Visual RecognitionarXiv:1310.1531Jeff Donahue, Yangqing Jia, Oriol Vinyals, et al.2013 · 3,463 citations
3. Lost in the Middle: How Language Models Use Long ContextsTransactions of the Association for Computational Linguistics (TACL)Nelson F. Liu, Kevin Lin, John Hewitt, et al.2023 · 2,584 citations
4. Kimi k1.5: Scaling Reinforcement Learning with LLMsarXiv:2501.12599Kimi Team, Angang Du, Bofei Gao, et al.2025 · 431 citations
5. A Review of Large Language Models and Autonomous Agents in ChemistryarXiv:2407.01603Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White2024 · 288 citations
6. 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
7. 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
8. SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language ModelarXiv:2502.02737Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.2025 · 181 citations
9. A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and TrustworthinessACM Transactions on Intelligent Systems and TechnologyFali Wang, Zhiwei Zhang, Xianren Zhang, et al.2024 · 159 citations
10. Generative Verifiers: Reward Modeling as Next-Token PredictionarXiv:2408.15240Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.2024 · 152 citations
11. Do latent tree learning models identify meaningful structure in sentences?Transactions of the Association for Computational Linguistics (TACL)Adina Williams, Andrew Drozdov, Samuel R. Bowman2018 · 149 citations
12. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
13. Fanar: An Arabic-Centric Multimodal Generative AI PlatformarXiv:2501.13944Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.2025 · 127 citations
14. OpenThoughts: Data Recipes for Reasoning ModelsarXiv:2506.04178Etash Guha, Ryan Marten, Sedrick Keh, et al.2025 · 122 citations
15. Do Long-Range Language Models Actually Use Long-Range Context?Conference on Empirical Methods in Natural Language Processing (EMNLP)Simeng Sun, Kalpesh Krishna, Andrew Mattarella-Micke, et al.2021 · 101 citations
16. FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every LanguagearXiv:2506.20920Guilherme Penedo, Hynek Kydliček, Vinko Sabolčec, et al.2025 · 99 citations
17. Make Your LLM Fully Utilize the ContextConference on Neural Information Processing Systems (NeurIPS)Shengnan An, Zexiong Ma, Zeqi Lin, et al.2024 · 97 citations
18. GLM-5: from Vibe Coding to Agentic EngineeringarXiv:2602.15763Aohan Zeng, Xin Lv, Zhenyu Hou, et al.2026 · 95 citations
19. 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
20. How to Train Long-Context Language Models (Effectively)Annual Meeting of the Association for Computational Linguistics (ACL)Tianyu Gao, Alexander Wettig, Howard Yen, et al.2025 · 89 citations
21. Small Language Models: Survey, Measurements, and InsightsarXiv:2409.15790Zhenyan Lu, Xiang Li, Dongqi Cai, et al.2024 · 88 citations
22. 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
23. Learning to Reason under Off-Policy GuidanceConference on Neural Information Processing Systems (NeurIPS)Jianhao Yan, Yafu Li, Zican Hu, et al.2025 · 68 citations
24. An Empirical Study of Mamba-based Language ModelsarXiv:2406.07887Roger Waleffe, Wonmin Byeon, Duncan Riach, et al.2024 · 67 citations
25. Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining DatasetAnnual Meeting of the Association for Computational Linguistics (ACL)Dan Su, Kezhi Kong, Ying Lin, et al.2025 · 65 citations
26. LAB-Bench: Measuring Capabilities of Language Models for Biology ResearcharXiv:2407.10362Jon M. Laurent, Joseph D. Janizek, Michael Ruzo, et al.2024 · 62 citations
27. mmBERT: A Modern Multilingual Encoder with Annealed Language LearningarXiv:2509.06888Marc Marone, Orion Weller, William Fleshman, et al.2025 · 59 citations
28. Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language ModelingarXiv:2406.07522Liliang Ren, Yang Liu, Yadong Lu, et al.2024 · 59 citations
29. 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
30. Generative Reward ModelsarXiv:2410.12832Dakota Mahan, Duy Van Phung, Rafael Rafailov, et al.2024 · 58 citations
31. RegMix: Data Mixture as Regression for Language Model Pre-trainingarXiv:2407.01492Qian Liu, Xiaosen Zheng, Niklas Muennighoff, et al.2024 · 57 citations
32. SmolVLM: Redefining small and efficient multimodal modelsarXiv:2504.05299Andres Marafioti, Orr Zohar, Miquel Farre, et al.2025 · 56 citations
33. Spurious Rewards: Rethinking Training Signals in RLVRarXiv:2506.10947Rulin Shao, Shuyue Stella Li, Rui Xin, et al.2025 · 53 citations
34. Kimi Linear: An Expressive, Efficient Attention ArchitecturearXiv:2510.26692Kimi Team, Yu Zhang, Zongyu Lin, et al.2025 · 51 citations
35. Hymba: A Hybrid-head Architecture for Small Language ModelsarXiv:2411.13676Xin Dong, Yonggan Fu, Shizhe Diao, et al.2024 · 50 citations
36. Zamba: A Compact 7B SSM Hybrid ModelarXiv:2405.16712Paolo Glorioso, Quentin Anthony, Yury Tokpanov, et al.2024 · 50 citations
37. Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language ModelsarXiv:2406.02061Marianna Nezhurina, Lucia Cipolina-Kun, Mehdi Cherti, et al.2024 · 48 citations
38. Scaling Laws with Vocabulary: Larger Models Deserve Larger VocabulariesarXiv:2407.13623Chaofan Tao, Qian Liu, Longxu Dou, et al.2024 · 46 citations
39. olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language ModelsarXiv:2502.18443Jake Poznanski, Aman Rangapur, Jon Borchardt, et al.2025 · 44 citations
40. Long-Context Language Modeling with Parallel Context EncodingAnnual Meeting of the Association for Computational Linguistics (ACL)Howard Yen, Tianyu Gao, Danqi Chen2024 · 44 citations
41. Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language ModelsarXiv:2502.17387Alon Albalak, Duy Phung, Nathan Lile, et al.2025 · 43 citations
42. Physics of Language Models: Part 1, Learning Hierarchical Language StructuresarXiv:2305.13673Zeyuan Allen-Zhu, Yuanzhi Li2023 · 42 citations
43. Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer ModelsarXiv:2504.03624NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.2025 · 38 citations
44. A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to ReproducibilityarXiv:2504.07086Andreas Hochlehnert, Hardik Bhatnagar, Vishaal Udandarao, et al.2025 · 36 citations
45. Morpho-syntactic Lexicon Generation Using Graph-based Semi-supervised LearningTransactions of the Association for Computational Linguistics (TACL)Manaal Faruqui, Ryan McDonald, Radu Soricut2016 · 31 citations
46. Towards Effective and Efficient Continual Pre-training of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jie Chen, Zhipeng Chen, Jiapeng Wang, et al.2025 · 29 citations
47. Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic ReasoningarXiv:2512.20848NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.2025 · 27 citations
48. Distillation Scaling LawsarXiv:2502.08606Dan Busbridge, Amitis Shidani, Floris Weers, et al.2025 · 26 citations
49. 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
50. Morphosyntactic probing of multilingual BERT modelsNatural Language EngineeringJudit Acs, Endre Hamerlik, Roy Schwartz, et al.2023 · 26 citations
51. RWKV-7 "Goose" with Expressive Dynamic State EvolutionarXiv:2503.14456Bo Peng, Ruichong Zhang, Daniel Goldstein, et al.2025 · 23 citations
52. MiniCPM4: Ultra-Efficient LLMs on End DevicesarXiv:2506.07900MiniCPM Team, Chaojun Xiao, Yuxuan Li, et al.2025 · 22 citations
53. Scaling Latent Reasoning via Looped Language ModelsarXiv:2510.25741Rui-Jie Zhu, Zixuan Wang, Kai Hua, et al.2025 · 22 citations
54. MegaMath: Pushing the Limits of Open Math CorporaarXiv:2504.02807Fan Zhou, Zengzhi Wang, Nikhil Ranjan, et al.2025 · 19 citations
55. RNNs are not Transformers (Yet): The Key Bottleneck on In-context RetrievalarXiv:2402.18510Kaiyue Wen, Xingyu Dang, Kaifeng Lyu2024 · 17 citations
56. 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
57. Can Large Reasoning Models Self-Train?arXiv:2505.21444Sheikh Shafayat, Fahim Tajwar, Ruslan Salakhutdinov, et al.2025 · 16 citations
58. Dataset Decomposition: Faster LLM Training with Variable Sequence Length CurriculumConference on Neural Information Processing Systems (NeurIPS)Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, et al.2024 · 16 citations
59. Outcome-based Exploration for LLM ReasoningarXiv:2509.06941Yuda Song, Julia Kempe, Remi Munos2025 · 15 citations
60. Rethinking Reflection in Pre-TrainingarXiv:2504.04022Essential AI: Darsh J Shah, Peter Rushton, Somanshu Singla, et al.2025 · 15 citations
61. Rewriting Pre-Training Data Boosts LLM Performance in Math and CodearXiv:2505.02881Kazuki Fujii, Yukito Tajima, Sakae Mizuki, et al.2025 · 15 citations
62. Mastering Board Games by External and Internal Planning with Language ModelsarXiv:2412.12119John Schultz, Jakub Adamek, Matej Jusup, et al.2024 · 14 citations
63. Maximize Your Data's Potential: Enhancing LLM Accuracy with Two-Phase PretrainingarXiv:2412.15285Steven Feng, Shrimai Prabhumoye, Kezhi Kong, et al.2024 · 12 citations
64. MiniPLM: Knowledge Distillation for Pre-Training Language ModelsarXiv:2410.17215Yuxian Gu, Hao Zhou, Fandong Meng, et al.2024 · 12 citations
65. Associative Recurrent Memory TransformerarXiv:2407.04841Ivan Rodkin, Yuri Kuratov, Aydar Bulatov, et al.2024 · 8 citations
66. ERNIE 5.0 Technical ReportarXiv:2602.04705Haifeng Wang, Hua Wu, Tian Wu, et al.2026 · 7 citations
67. Arabic Stable LM: Adapting Stable LM 2 1.6B to ArabicarXiv:2412.04277Zaid Alyafeai, Michael Pieler, Hannah Teufel, et al.2024 · 6 citations
68. Aleph-Alpha-GermanWeb: Improving German-language LLM pre-training with model-based data curation and synthetic data generationConference of the European Chapter of the Association for Computational Linguistics (EACL)Thomas F Burns, Letitia Parcalabescu, Stephan Waeldchen, et al.2026 · 4 citations
69. QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented GenerationFindings of the Association for Computational LinguisticsDehai Min, Kailin Zhang, Tongtong Wu, et al.2026 · 2 citations
70. The olmOCR Project: Building Fully Open OCR using VLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Jake Poznanski, Kyle Lo, Luca Soldaini2026 · 2 citations
71. Why Do More Experts Fail? A Theoretical Analysis of Model MergingAnnual Meeting of the Association for Computational Linguistics (ACL)Zijing Wang, Xingle Xu, YongKang Liu, et al.2026 · 2 citations
72. Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-trainingAnnual Meeting of the Association for Computational Linguistics (ACL)Kailai Yang, Xiao Liu, Lei Ji, et al.2026 · 1 citation
73. Improving Dialect Robustness in Large Language Models via LoRA and Mixture-of-ExpertsWorkshop on NLP for Similar Languages, Varieties and Dialects (VarDial)Sanjh Maheshwari, Aniket Singh Rajpoot, Oana Cocarascu, et al.2026 · 1 citation
74. Inferring Events from Time Series using Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mingtian Tan, Mike A Merrill, Zachary Gottesman, et al.2026 · 1 citation
75. KletterMix: Climbing Toward High-Quality German Pretraining Data - The Full ReportarXiv:2606.03773Maurice Kraus, Ruben Harle, Sebastian Sztwiertnia, et al.2026 · 1 citation
76. StateX: Enhancing RNN Recall via Post-training State ExpansionFindings of the Association for Computational LinguisticsXingyu Shen, Yingfa Chen, Zhen Leng Thai, et al.2026 · 1 citation
77. A Data-Efficient Path to Multilingual LLMs: Language Expansion via Post-training PARAMΔ Integration into Upcycled MoEAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Zhou, Tianhao Li, Zhijun Wang, et al.2026
78. A Survey on Parameter-efficient Fine-tuning of Large Models: Techniques, Trends, and Challenges (大模型参数高效微调方法综述: 技术、趋势与挑战)Acta Automatica Sinica (自动化学报)Anda Tang (唐岸达), Zhouchen Lin (林宙辰)2026
79. AuthorMix: Modular Authorship Style Transfer via Layer-wise Adapter MixingSarubi Thillainathan, Ji-Ung Lee, Michael Sullivan, et al.2026
80. Biomed-Enriched: Data-Efficient Biomedical Pretraining via Paragraph-Level AnnotationFindings of the Association for Computational LinguisticsRian Touchent, Nathan Godey, Éric Villemonte de la Clergerie2026
81. Dialectal Filtering: Synthesizing Kurdish Corpora for Low-Resource Varieties by Utilizing “Noise” in Large Textual DataLanguage Resources and Evaluation Conference (LREC)Christian Schuler, Raman Ahmad, Ānrán Wáng, et al.2026
82. Does RLVR Extend Reasoning Boundaries? Investigating Capability Expansion in Vision-Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Minghe Shen, Zhuo Zhi, Chonghan Liu, et al.2026
83. Don't Tell the Answer, Truly Guide the Reasoning During RL RolloutsFindings of the Association for Computational LinguisticsXinyi Wang, Jinyi Han, Zishang Jiang, et al.2026
84. EfficientLLM: Unified Pruning-Aware Pretraining for Auto-Designed Compact Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xingrun Xing, Zheng Liu, Shitao Xiao, et al.2026
85. FeedTrans: Enhance Machine Translation via FeedbackTransactions of the Association for Computational Linguistics (TACL)Zengkui Sun, Jiali Zeng, Jiaan Wang, et al.2026
86. GlossaGen: Making Academic Translation Smarter with GlossingFindings of the Association for Computational LinguisticsZixiao Wang, Duzhen Zhang, Juntian Zhang, et al.2026
87. How Can Synthetic Data Improve Multilingual Language Model Pretraining? A Data Quality PerspectiveAnnual Meeting of the Association for Computational Linguistics (ACL)Tongyao Zhu, Qian Liu, Chang Ma, et al.2026
88. Learning from Cognition: Enhancing RL Efficiency for LLM Reasoning via Hierarchical Metacognitive Decomposition and RefinementAnnual Meeting of the Association for Computational Linguistics (ACL)Zexu Sun, Yongcheng Zeng, Erxue Min, et al.2026
89. LEDOM: Reverse Language ModelAnnual Meeting of the Association for Computational Linguistics (ACL)Xunjian Yin, Sitao Cheng, Yuxi Xie, et al.2026
90. Mixed-Policy GRPO for Text-to-SQL with Off-Policy Data GenerationWorkshop on Structured Understanding, Retrieval, and Generation in the LLM EraMarko Sterbentz, Michael Glass, Nhan H Pham, et al.2026
91. On the Representation Geometry of LoRA Model MergingFindings of the Association for Computational LinguisticsChenyang Lu, Jiaru Li, Jinman Zhao, et al.2026
92. Probing the Dynamics of Syntactic Ability Acquisition Throughout LLM PretrainingHiroshi Matsuda, Masayuki Asahara2026
93. Rewriting History: A Recipe for Interventional Analyses to Study Data Effects on Model BehaviorTransactions of the Association for Computational Linguistics (TACL)Rahul Nadkarni, Yanai Elazar, Hila Gonen, et al.2026
94. SciPedia: Unlocking the Value of Scientific Data for Pre-trainingAnnual Meeting of the Association for Computational Linguistics (ACL)Yiwei Qin, Zhen Huang, Tiantian Mi, et al.2026
95. SELECting over Tokens: Curating Pre-training Data at Scale via Token ClassificationAnnual Meeting of the Association for Computational Linguistics (ACL)Xin Tong, Weidong Zhang, Jiaang Li, et al.2026
96. Systematic Evaluation of the Quality of Synthetic Clinical Notes Rephrased by LLMs at Million-Note ScaleBioNLPJinghui Liu, Sarvesh Soni, Anthony Nguyen2026
97. Tailored Primitive Initialization is the Secret Key to Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Yihang Yao, Guangtao Zeng, Raina Wu, et al.2026

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