🧑‍🔬 Who cites Samy Jelassi

148 citations of their works from 143 papers of our library (of the 149,439 whose bibliographies we read) · 47 with a page here, the most cited first · ← Samy Jelassi

1. Sparks of Artificial General Intelligence: Early experiments with GPT-4arXiv:2303.12712Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, et al.2023 · 2,439 citations
2. A Review of Large Language Models and Autonomous Agents in ChemistryarXiv:2407.01603Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White2024 · 288 citations
3. 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
4. TinyStories: How Small Can Language Models Be and Still Speak Coherent English?Ronen Eldan, Yuanzhi Li2023 · 213 citations
5. 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
6. Learning to Reason under Off-Policy GuidanceConference on Neural Information Processing Systems (NeurIPS)Jianhao Yan, Yafu Li, Zican Hu, et al.2025 · 68 citations
7. An Empirical Study of Mamba-based Language ModelsarXiv:2406.07887Roger Waleffe, Wonmin Byeon, Duncan Riach, et al.2024 · 67 citations
8. What Algorithms can Transformers Learn? A Study in Length GeneralizationarXiv:2310.16028Hattie Zhou, Arwen Bradley, Etai Littwin, et al.2023 · 67 citations
9. LAB-Bench: Measuring Capabilities of Language Models for Biology ResearcharXiv:2407.10362Jon M. Laurent, Joseph D. Janizek, Michael Ruzo, et al.2024 · 62 citations
10. Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language ModelingarXiv:2406.07522Liliang Ren, Yang Liu, Yadong Lu, et al.2024 · 59 citations
11. 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
12. Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning ProcessarXiv:2407.20311Tian Ye, Zicheng Xu, Yuanzhi Li, et al.2024 · 58 citations
13. Repeat After Me: Transformers are Better than State Space Models at CopyingarXiv:2402.01032Samy Jelassi, David Brandfonbrener, Sham M. Kakade, et al.2024 · 57 citations
14. Spurious Rewards: Rethinking Training Signals in RLVRarXiv:2506.10947Rulin Shao, Shuyue Stella Li, Rui Xin, et al.2025 · 53 citations
15. Kimi Linear: An Expressive, Efficient Attention ArchitecturearXiv:2510.26692Kimi Team, Yu Zhang, Zongyu Lin, et al.2025 · 51 citations
16. Hymba: A Hybrid-head Architecture for Small Language ModelsarXiv:2411.13676Xin Dong, Yonggan Fu, Shizhe Diao, et al.2024 · 50 citations
17. Zamba: A Compact 7B SSM Hybrid ModelarXiv:2405.16712Paolo Glorioso, Quentin Anthony, Yury Tokpanov, et al.2024 · 50 citations
18. Long-Context Language Modeling with Parallel Context EncodingAnnual Meeting of the Association for Computational Linguistics (ACL)Howard Yen, Tianyu Gao, Danqi Chen2024 · 44 citations
19. Physics of Language Models: Part 1, Learning Hierarchical Language StructuresarXiv:2305.13673Zeyuan Allen-Zhu, Yuanzhi Li2023 · 42 citations
20. GPT Can Solve Mathematical Problems Without a CalculatorarXiv:2309.03241Zhen Yang, Ming Ding, Qingsong Lv, et al.2023 · 41 citations
21. Transformers Can Do Arithmetic with the Right EmbeddingsConference on Neural Information Processing Systems (NeurIPS)Sean McLeish, Arpit Bansal, Alex Stein, et al.2024 · 36 citations
22. Positional Description Matters for Transformers ArithmeticarXiv:2311.14737Ruoqi Shen, Sébastien Bubeck, Ronen Eldan, et al.2023 · 30 citations
23. Transformers Can Achieve Length Generalization But Not RobustlyarXiv:2402.09371Yongchao Zhou, Uri Alon, Xinyun Chen, et al.2024 · 29 citations
24. Distillation Scaling LawsarXiv:2502.08606Dan Busbridge, Amitis Shidani, Floris Weers, et al.2025 · 26 citations
25. Global Lyapunov functions: a long-standing open problem in mathematics, with symbolic transformersConference on Neural Information Processing Systems (NeurIPS)Alberto Alfarano, François Charton, Amaury Hayat2024 · 19 citations
26. RNNs are not Transformers (Yet): The Key Bottleneck on In-context RetrievalarXiv:2402.18510Kaiyue Wen, Xingyu Dang, Kaifeng Lyu2024 · 17 citations
27. Outcome-based Exploration for LLM ReasoningarXiv:2509.06941Yuda Song, Julia Kempe, Remi Munos2025 · 15 citations
28. Chain-of-Thought Reasoning is a Policy Improvement OperatorarXiv:2309.08589Hugh Zhang, David C. Parkes2023 · 11 citations
29. Associative Recurrent Memory TransformerarXiv:2407.04841Ivan Rodkin, Yuri Kuratov, Aydar Bulatov, et al.2024 · 8 citations
30. SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-trainingarXiv:2310.02227Kazem Meidani, Parshin Shojaee, Chandan K. Reddy, et al.2023 · 8 citations
31. ERNIE 5.0 Technical ReportarXiv:2602.04705Haifeng Wang, Hua Wu, Tian Wu, et al.2026 · 7 citations
32. Improving Length-Generalization in Transformers via Task HintingarXiv:2310.00726Pranjal Awasthi, Anupam Gupta2023 · 7 citations
33. Explicitly Encoding Structural Symmetry is Key to Length Generalization in Arithmetic TasksarXiv:2406.01895Mahdi Sabbaghi, George Pappas, Hamed Hassani, et al.2024 · 5 citations
34. 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
35. 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
36. 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
37. 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
38. 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
39. AuthorMix: Modular Authorship Style Transfer via Layer-wise Adapter MixingSarubi Thillainathan, Ji-Ung Lee, Michael Sullivan, et al.2026
40. 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
41. 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
42. FeedTrans: Enhance Machine Translation via FeedbackTransactions of the Association for Computational Linguistics (TACL)Zengkui Sun, Jiali Zeng, Jiaan Wang, et al.2026
43. GlossaGen: Making Academic Translation Smarter with GlossingFindings of the Association for Computational LinguisticsZixiao Wang, Duzhen Zhang, Juntian Zhang, et al.2026
44. 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
45. 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
46. On the Representation Geometry of LoRA Model MergingFindings of the Association for Computational LinguisticsChenyang Lu, Jiaru Li, Jinman Zhao, et al.2026
47. 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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