🧑‍🔬 Who cites Yi Su

172 citations of their works from 172 papers of our library (of the 149,439 whose bibliographies we read) · 37 with a page here, the most cited first · ← Yi Su

1. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement LearningNatureDeepSeek-AI, Daya Guo, Dejian Yang, et al.2025 · 4,728 citations
2. Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement LearningarXiv:2503.09516Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.2025 · 322 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. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
5. rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep ThinkingarXiv:2501.04519Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al.2025 · 146 citations
6. Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRsarXiv:2503.01307Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.2025 · 123 citations
7. A Peek into Token Bias: Large Language Models Are Not Yet Genuine ReasonersConference on Empirical Methods in Natural Language Processing (EMNLP)Bowen Jiang, Yangxinyu Xie, Zhuoqun Hao, et al.2024 · 64 citations
8. From Decoding to Meta-Generation: Inference-time Algorithms for Large Language ModelsarXiv:2406.16838Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.2024 · 51 citations
9. RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement LearningarXiv:2410.02089Jonas Gehring, Kunhao Zheng, Jade Copet, et al.2024 · 51 citations
10. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations
11. Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?Annual Meeting of the Association for Computational Linguistics (ACL)Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.2025 · 38 citations
12. S²R: Teaching LLMs to Self-verify and Self-correct via Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Ruotian Ma, Peisong Wang, Cheng Liu, et al.2025 · 26 citations
13. How Is LLM Reasoning Distracted by Irrelevant Context? An Analysis Using a Controlled BenchmarkMinglai Yang, Ethan Huang, Liang Zhang, et al.2025 · 25 citations
14. Online Difficulty Filtering for Reasoning Oriented Reinforcement LearningConference of the European Chapter of the Association for Computational Linguistics (EACL)Sanghwan Bae, Jiwoo Hong, Min Young Lee, et al.2026 · 22 citations
15. MindSearch: Mimicking Human Minds Elicits Deep AI SearcherarXiv:2407.20183Zehui Chen, Kuikun Liu, Qiuchen Wang, et al.2024 · 20 citations
16. A Survey of Post-Training Scaling in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Hanyu Lai, Xiao Liu, Junjie Gao, et al.2025 · 18 citations
17. Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language ModelsarXiv:2503.24377Rui Wang, Hongru Wang, Boyang Xue, et al.2025 · 16 citations
18. FR-Spec: Accelerating Large-Vocabulary Language Models via Frequency-Ranked Speculative SamplingAnnual Meeting of the Association for Computational Linguistics (ACL)Weilin Zhao, Tengyu Pan, Xu Han, et al.2025 · 15 citations
19. MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Chanwoo Park, Seungju Han, Xingzhi Guo, et al.2025 · 15 citations
20. From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical DebuggingarXiv:2410.01215Yuling Shi, Songsong Wang, Chengcheng Wan, et al.2024 · 15 citations
21. Confidence v.s. Critique: A Decomposition of Self-Correction Capability for LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhe Yang, Yichang Zhang, Yudong Wang, et al.2025 · 11 citations
22. TESS 2: A Large-Scale Generalist Diffusion Language ModelAnnual Meeting of the Association for Computational Linguistics (ACL)Jaesung Tae, Hamish Ivison, Sachin Kumar, et al.2025 · 9 citations
23. PAG: Multi-Turn Reinforced LLM Self-Correction with Policy as Generative VerifierarXiv:2506.10406Yuhua Jiang, Yuwen Xiong, Yufeng Yuan, et al.2025 · 8 citations
24. R-Search: Empowering LLM Reasoning with Search via Multi-Reward Reinforcement LearningFindings of the Association for Computational LinguisticsQingfei Zhao, Ruobing Wang, Dingling Xu, et al.2026 · 7 citations
25. LogitSpec: Accelerating Retrieval-based Speculative Decoding via Next Next Token SpeculationFindings of the Association for Computational LinguisticsTianyu Liu, Qitan Lv, Hao Li, et al.2026 · 6 citations
26. Don't Act Blindly: Robust GUI Automation via Action-Effect Verification and Self-CorrectionAnnual Meeting of the Association for Computational Linguistics (ACL)Yuzhe Zhang, Xianwei Xue, Xingyong Wu, et al.2026 · 5 citations
27. Language-Coupled Reinforcement Learning for Multilingual Retrieval-Augmented GenerationFindings of the Association for Computational LinguisticsRui Qi, Fengran Mo, Yufeng Chen, et al.2026 · 5 citations
28. From Belief Entrenchment to Robust Reasoning in LLM AgentsTransactions of the Association for Computational Linguistics (TACL)Jihwan Oh, Minchan Jeong, Jongwoo Ko, et al.2026 · 2 citations
29. Sparrow: Text-Anchored Window Attention with Visual-Semantic Glimpsing for Speculative Decoding in Video LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Libo Zhang, Zhaoning Zhang, Hongwanyang, et al.2026 · 2 citations
30. Correct, Concise and Complete: Multi-stage Training For Adaptive ReasoningFindings of the Association for Computational LinguisticsNathanaël Carraz Rakotonirina, Ren Pang, Neha Anna John, et al.2026 · 1 citation
31. Meeseeks: A Feedback-Driven, Iterative Self-Correction Benchmark evaluating LLMs' Instruction Following CapabilityFindings of the Association for Computational LinguisticsJiaming Wang, Yunke Zhao, Peng Ding, et al.2026 · 1 citation
32. Reasoning or Knowledge: Stratified Evaluation of Biomedical LLMsConference of the European Chapter of the Association for Computational Linguistics (EACL)Rahul Thapa, Qingyang Wu, Kevin Wu, et al.2026 · 1 citation
33. Robust Tool Use via Fission-GRPO: Learning to Recover from Execution ErrorsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiwei Zhang, Fei Zhao, Rui Wang, et al.2026 · 1 citation
34. Beyond Memorization: Extending Reasoning Depth with Recurrence, Memory and Test-Time Compute ScalingFindings of the Association for Computational LinguisticsIvan Rodkin, Daniil Orel, Konstantin Smirnov, et al.2026
35. Can LLMs Self-Correct Table Reasoning Errors?Workshop on Structured Understanding, Retrieval, and Generation in the LLM EraFarseen Shaikh2026
36. Self-Reflective Generation at Test TimeAnnual Meeting of the Association for Computational Linguistics (ACL)Jian Mu, Qixin Zhang, Zhiyong Wang, et al.2026
37. ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Vladislav Smirnov, Quang-Chieu Nguyen, Sergey Senichev, et al.2026

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