🧑‍🔬 Who cites Eran Malach

111 citations of their works from 110 papers of our library (of the 149,439 whose bibliographies we read) · 36 with a page here, the most cited first · ← Eran Malach

1. A Review of Large Language Models and Autonomous Agents in ChemistryarXiv:2407.01603Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White2024 · 288 citations
2. 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
3. Generative Verifiers: Reward Modeling as Next-Token PredictionarXiv:2408.15240Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.2024 · 152 citations
4. 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
5. Learning to Reason under Off-Policy GuidanceConference on Neural Information Processing Systems (NeurIPS)Jianhao Yan, Yafu Li, Zican Hu, et al.2025 · 68 citations
6. An Empirical Study of Mamba-based Language ModelsarXiv:2406.07887Roger Waleffe, Wonmin Byeon, Duncan Riach, et al.2024 · 67 citations
7. LAB-Bench: Measuring Capabilities of Language Models for Biology ResearcharXiv:2407.10362Jon M. Laurent, Joseph D. Janizek, Michael Ruzo, et al.2024 · 62 citations
8. Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language ModelingarXiv:2406.07522Liliang Ren, Yang Liu, Yadong Lu, et al.2024 · 59 citations
9. 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
10. Spurious Rewards: Rethinking Training Signals in RLVRarXiv:2506.10947Rulin Shao, Shuyue Stella Li, Rui Xin, et al.2025 · 53 citations
11. Kimi Linear: An Expressive, Efficient Attention ArchitecturearXiv:2510.26692Kimi Team, Yu Zhang, Zongyu Lin, et al.2025 · 51 citations
12. Hymba: A Hybrid-head Architecture for Small Language ModelsarXiv:2411.13676Xin Dong, Yonggan Fu, Shizhe Diao, et al.2024 · 50 citations
13. Zamba: A Compact 7B SSM Hybrid ModelarXiv:2405.16712Paolo Glorioso, Quentin Anthony, Yury Tokpanov, et al.2024 · 50 citations
14. Long-Context Language Modeling with Parallel Context EncodingAnnual Meeting of the Association for Computational Linguistics (ACL)Howard Yen, Tianyu Gao, Danqi Chen2024 · 44 citations
15. Physics of Language Models: Part 1, Learning Hierarchical Language StructuresarXiv:2305.13673Zeyuan Allen-Zhu, Yuanzhi Li2023 · 42 citations
16. Distillation Scaling LawsarXiv:2502.08606Dan Busbridge, Amitis Shidani, Floris Weers, et al.2025 · 26 citations
17. RNNs are not Transformers (Yet): The Key Bottleneck on In-context RetrievalarXiv:2402.18510Kaiyue Wen, Xingyu Dang, Kaifeng Lyu2024 · 17 citations
18. Can Large Reasoning Models Self-Train?arXiv:2505.21444Sheikh Shafayat, Fahim Tajwar, Ruslan Salakhutdinov, et al.2025 · 16 citations
19. Outcome-based Exploration for LLM ReasoningarXiv:2509.06941Yuda Song, Julia Kempe, Remi Munos2025 · 15 citations
20. Mastering Board Games by External and Internal Planning with Language ModelsarXiv:2412.12119John Schultz, Jakub Adamek, Matej Jusup, et al.2024 · 14 citations
21. Associative Recurrent Memory TransformerarXiv:2407.04841Ivan Rodkin, Yuri Kuratov, Aydar Bulatov, et al.2024 · 8 citations
22. ERNIE 5.0 Technical ReportarXiv:2602.04705Haifeng Wang, Hua Wu, Tian Wu, et al.2026 · 7 citations
23. 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
24. 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
25. 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
26. 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
27. 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
28. AuthorMix: Modular Authorship Style Transfer via Layer-wise Adapter MixingSarubi Thillainathan, Ji-Ung Lee, Michael Sullivan, et al.2026
29. 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
30. 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
31. FeedTrans: Enhance Machine Translation via FeedbackTransactions of the Association for Computational Linguistics (TACL)Zengkui Sun, Jiali Zeng, Jiaan Wang, et al.2026
32. GlossaGen: Making Academic Translation Smarter with GlossingFindings of the Association for Computational LinguisticsZixiao Wang, Duzhen Zhang, Juntian Zhang, et al.2026
33. 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
34. 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
35. On the Representation Geometry of LoRA Model MergingFindings of the Association for Computational LinguisticsChenyang Lu, Jiaru Li, Jinman Zhao, et al.2026
36. 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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