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Who cites Ramana Kumar

371 citations of their works from 370 papers of our library (of the 149,439 whose bibliographies we read) · 164 with a page here, the most cited first · page 2 of 2 · 101–164 · ← Ramana Kumar

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  1. Positional Description Matters for Transformers ArithmeticarXiv:2311.14737Ruoqi Shen, Sébastien Bubeck, Ronen Eldan, et al.2023 · 30 citations
  2. Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal SamplingarXiv:2408.16737Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.2024 · 27 citations
  3. Scaling Test-Time Compute Without Verification or RL is SuboptimalarXiv:2502.12118Amrith Setlur, Nived Rajaraman, Sergey Levine, et al.2025 · 26 citations
  4. How Is LLM Reasoning Distracted by Irrelevant Context? An Analysis Using a Controlled BenchmarkMinglai Yang, Ethan Huang, Liang Zhang, et al.2025 · 25 citations
  5. TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement LearningarXiv:2102.09756Minchao Wu, Michael Norrish, Christian Walder, et al.2021 · 24 citations
  6. LEAN-GitHub: Compiling GitHub LEAN repositories for a versatile LEAN proverarXiv:2407.17227Zijian Wu, Jiayu Wang, Dahua Lin, et al.2024 · 23 citations
  7. AI Sandbagging: Language Models can Strategically Underperform on EvaluationsarXiv:2406.07358Teun van der Weij, Felix Hofstatter, Ollie Jaffe, et al.2024 · 22 citations
  8. Self-Evolving Curriculum for LLM ReasoningarXiv:2505.14970Xiaoyin Chen, Jiarui Lu, Minsu Kim, et al.2025 · 20 citations
  9. Aviary: training language agents on challenging scientific tasksarXiv:2412.21154Siddharth Narayanan, James D. Braza, Ryan-Rhys Griffiths, et al.2024 · 18 citations
  10. 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
  11. Preference Optimization for Reasoning with Pseudo FeedbackarXiv:2411.16345Fangkai Jiao, Geyang Guo, Xingxing Zhang, et al.2024 · 15 citations
  12. Understanding Chain-of-Thought in LLMs through Information TheoryarXiv:2411.11984Jean-Francois Ton, Muhammad Faaiz Taufiq, Yang Liu2024 · 14 citations
  13. EventRL: Enhancing Event Extraction with Outcome Supervision for Large Language ModelsarXiv:2402.11430Jun Gao, Huan Zhao, Wei Wang, et al.2024 · 11 citations
  14. Design of Chain-of-Thought in Math Problem SolvingarXiv:2309.11054Zhanming Jie, Trung Quoc Luong, Xinbo Zhang, et al.2023 · 10 citations
  15. Antidistillation SamplingConference on Neural Information Processing Systems (NeurIPS)Yash Savani, Asher Trockman, Zhili Feng, et al.2025 · 9 citations
  16. Unmasking On-Policy Distillation: Where It Helps, Where It Hurts, and WhyarXiv:2605.10889Mohammadreza Armandpour, Fatih Ilhan, David Harrison, et al.2026 · 7 citations
  17. A Survey on Feedback-based Multi-step Reasoning for Large Language Models on MathematicsarXiv:2502.14333Ting-Ruen Wei, Haowei Liu, Xuyang Wu, et al.2025 · 7 citations
  18. 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
  19. Position: Correct Answer, Wrong Mechanism — When AI Scientists Defend General Claims Their Own Data ContradictsarXiv:2606.23175Steven Young Eulig2026 · 1 citation

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