🧑‍🔬 Who cites Mehul Damani

140 citations of their works from 138 papers of our library (of the 149,439 whose bibliographies we read) · 41 with a page here, the most cited first · ← Mehul Damani

1. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement LearningNatureDeepSeek-AI, Daya Guo, Dejian Yang, et al.2025 · 4,728 citations
2. Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language ModelsComputational LinguisticsYue Zhang, Yafu Li, Leyang Cui, et al.2023 · 977 citations
3. Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMsarXiv:2412.21187Xingyu Chen, Jiahao Xu, Tian Liang, et al.2024 · 192 citations
4. Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language ModelsarXiv:2601.18734Siyan Zhao, Zhihui Xie, Mengchen Liu, et al.2026 · 97 citations
5. TTRL: Test-Time Reinforcement LearningConference on Neural Information Processing Systems (NeurIPS)Yuxin Zuo, Kaiyan Zhang, Li Sheng, et al.2025 · 76 citations
6. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
7. Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and RecipearXiv:2604.13016Yaxuan Li, Yuxin Zuo, Bingxiang He, et al.2026 · 58 citations
8. Reasoning Models Know When They're Right: Probing Hidden States for Self-VerificationarXiv:2504.05419Anqi Zhang, Yulin Chen, Jane Pan, et al.2025 · 52 citations
9. A Survey of On-Policy Distillation for Large Language ModelsarXiv:2604.00626Mingyang Song, Mao Zheng2026 · 41 citations
10. 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
11. Self-Distilled RLVRarXiv:2604.03128Chenxu Yang, Chuanyu Qin, Qingyi Si, et al.2026 · 37 citations
12. On-Policy Context Distillation for Language ModelsarXiv:2602.12275Tianzhu Ye, Li Dong, Xun Wu, et al.2026 · 36 citations
13. The Surprising Effectiveness of Test-Time Training for Few-Shot LearningarXiv:2411.07279Ekin Akyürek, Mehul Damani, Adam Zweiger, et al.2024 · 36 citations
14. Aristotle: IMO-level Automated Theorem ProvingSuperIntelligence - Robotics - Safety & AlignmentTudor Achim, Alex Best, Alberto Bietti, et al.2025 · 29 citations
15. Training a Scientific Reasoning Model for ChemistryarXiv:2506.17238Siddharth M. Narayanan, James D. Braza, Ryan-Rhys Griffiths, et al.2025 · 15 citations
16. Is That Your Final Answer? Test-Time Scaling Improves Selective Question AnsweringAnnual Meeting of the Association for Computational Linguistics (ACL)William Jurayj, Jeffrey Cheng, Benjamin Van Durme2025 · 11 citations
17. Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy DistillationarXiv:2604.13010Yecheng Wu, Song Han, Han Cai2026 · 10 citations
18. KL for a KL: On-Policy Distillation with Control Variate BaselinearXiv:2605.07865Minjae Oh, Sangjun Song, Gyubin Choi, et al.2026 · 8 citations
19. Unmasking On-Policy Distillation: Where It Helps, Where It Hurts, and WhyarXiv:2605.10889Mohammadreza Armandpour, Fatih Ilhan, David Harrison, et al.2026 · 7 citations
20. Asymmetric On-Policy Distillation: Bridging Exploitation and Imitation at the Token LevelarXiv:2605.06387Nan Jia, Haojin Yang, Xing Ma, et al.2026 · 6 citations
21. Uni-OPD: Unifying On-Policy Distillation with a Dual-Perspective RecipearXiv:2605.03677Wenjin Hou, Shangpin Peng, Weinong Wang, et al.2026 · 6 citations
22. Making Small Language Models Efficient Reasoners: Intervention, Supervision, ReinforcementarXiv:2505.07961Xuechen Zhang, Zijian Huang, Chenshun Ni, et al.2025 · 6 citations
23. Self-Distilled Policy GradientarXiv:2606.04036Yifeng Liu, Shiyuan Zhang, Yifan Zhang, et al.2026 · 5 citations
24. Gated Differentiable Working Memory for Long-Context Language ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.2026 · 4 citations
25. Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Yuming Yang, Mingyoung Lai, Wanxu Zhao, et al.2026 · 4 citations
26. Beyond “I Don't Know”: Evaluating LLM Self-Awareness in Discriminating Data and Model UncertaintyAnnual Meeting of the Association for Computational Linguistics (ACL)Jingyi Ren, Ante Wang, Yunghwei Lai, et al.2026 · 3 citations
27. The Confidence Dichotomy: Analyzing and Mitigating Miscalibration in Tool-Use AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Weihao Xuan, Qingcheng Zeng, Heli Qi, et al.2026 · 2 citations
28. Confidence-Calibrated Small-Large Language Model Collaboration for Cost-Efficient ReasoningConference of the European Chapter of the Association for Computational Linguistics (EACL)Chuang Zhang, Zizhen Zhu, Yihao Wei, et al.2026 · 1 citation
29. GlimpRouter: Efficient Collaborative Inference by Glimpsing One Token of ThoughtsFindings of the Association for Computational LinguisticsWenhao Zeng, Xuteng Zhang, Yuling Shi, et al.2026 · 1 citation
30. LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?Annual Meeting of the Association for Computational Linguistics (ACL)Jingyuan Wang, Yankai Chen, Zhonghang Li, et al.2026 · 1 citation
31. Adaptive Test-Time Compute Allocation with Evolving In-Context DemonstrationsFindings of the Association for Computational LinguisticsBowen Zuo, Dongruo Zhou, Yinglun Zhu2026
32. Balancing Classification and Calibration Performance in Decision-Making LLMs via Calibration Aware Reinforcement LearningFindings of the Association for Computational LinguisticsDuygu Nur Yaldiz, Evangelia Spiliopoulou, Zheng Qi, et al.2026
33. Calibrating LLM Judges: Linear Probes for Fast and Reliable Uncertainty EstimationAnnual Meeting of the Association for Computational Linguistics (ACL)Bhaktipriya Radharapu, Eshika Saxena, Kenneth Li, et al.2026
34. Calibration-Aware Policy Optimization for Reasoning LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Ziqi Wang, Xingzhou Lou, Meiqi Wu, et al.2026
35. Distill and Align Decomposition for Enhanced Claim VerificationFindings of the Association for Computational LinguisticsJabez Magomere, Elena Kochkina, Samuel Mensah, et al.2026
36. EpiCaR: Knowing What You Don't Know Matters for Better Reasoning in LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Jewon Yeom, Jaewon Sok, Seonghyeon Park, et al.2026
37. Illusions of Confidence? Diagnosing LLM Truthfulness via Neighborhood ConsistencyAnnual Meeting of the Association for Computational Linguistics (ACL)Haoming Xu, Ningyuan Zhao, Yunzhi Yao, et al.2026
38. Test-Time Training for Zero-Resource Dense Retrieval RerankingWorkshop on Towards Knowledgeable Foundation ModelsShiyan Liu, Yichen Li2026
39. Think Hard Only When Needed: A Hybrid Best-of-N and Beam Search for Efficient Test-Time ComputeFindings of the Association for Computational LinguisticsHyewon Suh, Chaojian Li, Cheng-Jhih Shih, et al.2026
40. VL-Calibration: Decoupled Confidence Calibration for Large Vision-Language Models ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Wenyi Xiao, Xinchi XU, Leilei Gan2026
41. Your Reasoning Benchmark May Not Test Reasoning: Revealing Perception Bottleneck in Abstract Reasoning BenchmarksAnnual Meeting of the Association for Computational Linguistics (ACL)Xinhe Wang, Jin Huang, Xingjian Zhang, et al.2026

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