🧑‍🔬 Who cites Yiwei Qin

198 citations of their works from 197 papers of our library (of the 149,439 whose bibliographies we read) · 71 with a page here, the most cited first · ← Yiwei Qin

1. s1: Simple test-time scalingConference on Empirical Methods in Natural Language Processing (EMNLP)Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.2025 · 608 citations
2. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 520 citations
3. Search-o1: Agentic Search-Enhanced Large Reasoning ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Xiaoxi Li, Guanting Dong, Jiajie Jin, et al.2025 · 211 citations
4. LIMO: Less is More for ReasoningarXiv:2502.03387Yixin Ye, Zhen Huang, Yang Xiao, et al.2025 · 209 citations
5. 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
6. Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language ModelsarXiv:2501.09686Fengli Xu, Qianyue Hao, Zefang Zong, et al.2025 · 120 citations
7. WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the WildarXiv:2406.04770Bill Yuchen Lin, Yuntian Deng, Khyathi Chandu, et al.2024 · 105 citations
8. ToolRL: Reward is All Tool Learning NeedsarXiv:2504.13958Cheng Qian, Emre Can Acikgoz, Qi He, et al.2025 · 94 citations
9. HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMsarXiv:2412.18925Junying Chen, Zhenyang Cai, Ke Ji, et al.2024 · 87 citations
10. A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?arXiv:2503.24235Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.2025 · 79 citations
11. WebThinker: Empowering Large Reasoning Models with Deep Research CapabilityConference on Neural Information Processing Systems (NeurIPS)Xiaoxi Li, Jiajie Jin, Guanting Dong, et al.2025 · 72 citations
12. Imitate, Explore, and Self-Improve: A Reproduction Report on Slow-thinking Reasoning SystemsarXiv:2412.09413Yingqian Min, Zhipeng Chen, Jinhao Jiang, et al.2024 · 66 citations
13. A Comprehensive Survey on Long Context Language ModelingarXiv:2503.17407Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.2025 · 64 citations
14. PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mingyang Song, Zhaochen Su, Xiaoye Qu, et al.2025 · 63 citations
15. ToRL: Scaling Tool-Integrated RLarXiv:2503.23383Xuefeng Li, Haoyang Zou, Pengfei Liu2025 · 61 citations
16. Generalizing Verifiable Instruction FollowingConference on Neural Information Processing Systems (NeurIPS)Valentina Pyatkin, Saumya Malik, Victoria Graf, et al.2025 · 59 citations
17. Agentic Reasoning: A Streamlined Framework for Enhancing LLM Reasoning with Agentic ToolsAnnual Meeting of the Association for Computational Linguistics (ACL)Junde Wu, Jiayuan Zhu, Yuyuan Liu, et al.2025 · 45 citations
18. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations
19. Conifer: Improving Complex Constrained Instruction-Following Ability of Large Language ModelsarXiv:2404.02823Haoran Sun, Lixin Liu, Junjie Li, et al.2024 · 40 citations
20. 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
21. Checklists Are Better Than Reward Models For Aligning Language ModelsConference on Neural Information Processing Systems (NeurIPS)Vijay Viswanathan, Yanchao Sun, Shuang Ma, et al.2025 · 37 citations
22. Direct Judgement Preference OptimizationConference on Empirical Methods in Natural Language Processing (EMNLP)PeiFeng Wang, Austin Xu, Yilun Zhou, et al.2025 · 35 citations
23. CFBench: A Comprehensive Constraints-Following Benchmark for LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Tao Zhang, ChengLIn Zhu, Yanjun Shen, et al.2025 · 30 citations
24. 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
25. OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Tianci Liu, Ran Xu, Tony Yu, et al.2026 · 25 citations
26. R1-T1: Fully Incentivizing Translation Capability in LLMs via Reasoning LearningTransactions of the Association for Computational Linguistics (TACL)Minggui He, Yilun Liu, Shimin Tao, et al.2026 · 22 citations
27. 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
28. IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Xinghua Zhang, Haiyang Yu, Cheng Fu, et al.2025 · 14 citations
29. Long-Short Chain-of-Thought Mixture Supervised Fine-Tuning Eliciting Efficient Reasoning in Large Language ModelsarXiv:2505.03469Bin Yu, Hang Yuan, Haotian Li, et al.2025 · 13 citations
30. Scaling Reasoning, Losing Control: Evaluating Instruction Following in Large Reasoning ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Tingchen Fu, Yafu Li, Jiawei Gu, et al.2026 · 12 citations
31. Mitigating Visual Forgetting via Take-along Visual Conditioning for Multi-modal Long CoT ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Hai-Long Sun, Zhun Sun, Houwen Peng, et al.2025 · 12 citations
32. LIFBench: Evaluating the Instruction Following Performance and Stability of Large Language Models in Long-Context ScenariosAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaodong Wu, Minhao Wang, Yichen Liu, et al.2025 · 11 citations
33. ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Yu Sun, Xingyu Qian, Weiwen Xu, et al.2025 · 11 citations
34. SaRO: Enhancing LLM Safety through Reasoning-based AlignmentarXiv:2504.09420Yutao Mou, Yuxiao Luo, Shikun Zhang, et al.2025 · 11 citations
35. Beyond Distillation: Pushing the Limits of Medical LLM Reasoning with Minimalist Rule-Based RLarXiv:2505.17952Che Liu, Haozhe Wang, Jiazhen Pan, et al.2025 · 10 citations
36. RoT: Enhancing Table Reasoning with Iterative Row-Wise TraversalsConference on Empirical Methods in Natural Language Processing (EMNLP)Xuanliang Zhang, Dingzirui Wang, Keyan Xu, et al.2025 · 10 citations
37. Do LLMs Really Think Step-by-step In Implicit Reasoning?arXiv:2411.15862Yijiong Yu2024 · 10 citations
38. AdvancedIF: Rubric-Based Benchmarking and Reinforcement Learning for Advancing LLM Instruction FollowingAnnual Meeting of the Association for Computational Linguistics (ACL)Yun He, Wenzhe Li, Hejia Zhang, et al.2026 · 9 citations
39. Nemotron-CrossThink: Scaling Self-Learning beyond Math ReasoningConference of the European Chapter of the Association for Computational Linguistics (EACL)Syeda Nahida Akter, Shrimai Prabhumoye, Matvei Novikov, et al.2026 · 9 citations
40. TemplateRL: Structured Template-Guided Reinforcement Learning for LLM ReasoningFindings of the Association for Computational LinguisticsJinyang Wu, Chonghua Liao, Mingkuan Feng, et al.2026 · 8 citations
41. Marco-o1 v2: Towards Widening The Distillation Bottleneck for Reasoning ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Huifeng Yin, Yu Zhao, Minghao Wu, et al.2025 · 8 citations
42. DiagnosisArena: Benchmarking Diagnostic Reasoning for Large Language ModelsFindings of the Association for Computational LinguisticsYakun Zhu, Zhongzhen Huang, Linjie Mu, et al.2026 · 7 citations
43. UltraIF: Advancing Instruction Following from the WildConference on Empirical Methods in Natural Language Processing (EMNLP)Kaikai An, Li Sheng, Ganqu Cui, et al.2025 · 7 citations
44. What Prompts Don't Say: Understanding and Managing Underspecification in LLM PromptsFindings of the Association for Computational LinguisticsChenyang Yang, Yike Shi, Qianou Ma, et al.2026 · 6 citations
45. FineReason: Evaluating and Improving LLMs' Deliberate Reasoning through Reflective Puzzle SolvingAnnual Meeting of the Association for Computational Linguistics (ACL)Guizhen Chen, Weiwen Xu, Hao Zhang, et al.2025 · 6 citations
46. Embodied-Reasoner: Synergizing Visual Search, Reasoning, and Action for Embodied Interactive TasksAnnual Meeting of the Association for Computational Linguistics (ACL)Wenqi Zhang, Mengna Wang, Gangao Liu, et al.2026 · 5 citations
47. EIFBENCH: Extremely Complex Instruction Following Benchmark for Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Tao Zou, Xinghua Zhang, Haiyang Yu, et al.2025 · 5 citations
48. MulDimIF: A Multi-Dimensional Constraint Framework for Evaluating and Improving Instruction Following in Large Language ModelsFindings of the Association for Computational LinguisticsJunjie Ye, Caishuang Huang, Zhuohan Chen, et al.2026 · 4 citations
49. OctoBench: Benchmarking Scaffold-Aware Instruction Following in Repository-Grounded Agentic CodingAnnual Meeting of the Association for Computational Linguistics (ACL)Deming Ding, Shichun Liu, Enhui Yang, et al.2026 · 4 citations
50. Spotlight Your Instructions: Instruction-following with Dynamic Attention SteeringConference of the European Chapter of the Association for Computational Linguistics (EACL)Praveen Venkateswaran, Danish Contractor2026 · 4 citations
51. MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive TrainingAnnual Meeting of the Association for Computational Linguistics (ACL)Hui Huang, Jiaheng Liu, Yancheng He, et al.2025 · 4 citations
52. a1: Steep Test-time Scaling Law via Environment Augmented GenerationFindings of the Association for Computational LinguisticsLingrui Mei, Shenghua Liu, Yiwei Wang, et al.2026 · 2 citations
53. KCIF: Knowledge-Conditioned Instruction FollowingLanguage Resources and Evaluation Conference (LREC)Rudra Murthy, Praveen Venkateswaran, Prince Kumar, et al.2026 · 2 citations
54. IF-RewardBench: Benchmarking Judge Models for Instruction-Following EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Bosi Wen, Yilin Niu, Cunxiang Wang, et al.2026 · 1 citation
55. 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
56. SCAN: Structured Capability Assessment and Navigation for LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Zongqi Wang, Tianle Gu, Chen Gong, et al.2026 · 1 citation
57. AutoChecklist: Composable Pipelines for Checklist Generation and Scoring with LLM-as-a-JudgeAnnual Meeting of the Association for Computational Linguistics (ACL)Karen Zhou, Chenhao Tan2026
58. Beyond Examples: Towards Automated Thought-level In-Context Reasoning for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jinyang Wu, Mingkuan Feng, Shuai Zhang, et al.2026
59. Beyond Simple Term Injection: Reasoning Models for Legal Translation in a Non-Dominant Language VarietyAnnual Conference of the European Association for Machine Translation (EAMT)Paolo Di Natale, Elena Chiocchetti, Marlies Alber, et al.2026
60. Complex-IF and Beyond: Expert Rubrics for RLVRWorkshop on Generation, Evaluation and Metrics (GEM)Sushant Mehta, Liudas Panavas, Eleanor Fleming, et al.2026
61. DAC-Bench: A Decision-Aware Benchmark for Compositional Mobile GUI TasksAnnual Meeting of the Association for Computational Linguistics (ACL)Yuqing Zhang, Honghui Sheng, Xueyu Hu, et al.2026
62. Deconstructing Instruction-Following: A New Benchmark for Granular Evaluation of Large Language Model Instruction Compliance AbilitiesConference of the European Chapter of the Association for Computational Linguistics (EACL)Alberto Purpura, Li Wang, Sahil Badyal, et al.2026
63. ImpRIF: Stronger Implicit Reasoning Leads to Better Complex Instruction FollowingAnnual Meeting of the Association for Computational Linguistics (ACL)Yuancheng Yang, Lin Yang, Xu Wang, et al.2026
64. InstructSum: A Benchmark to Evaluate Instruction-Following Capability of Large Language Models in SummarizationLanguage Resources and Evaluation Conference (LREC)Kosuke Nishida, Kyosuke Nishida, Itsumi Saito2026
65. PARIF: Pushing the Pareto Frontier of Instruction Following and Reasoning with Curriculum Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Rongchuan Mu, Zexin Wang, Qianyu Wang, et al.2026
66. R ESEARCH QA: Evaluating Scholarly Question Answering at Scale Across 75 Fields with Survey-Mined Questions and RubricsTransactions of the Association for Computational Linguistics (TACL)Li S. Yifei, Allen Chang, Chaitanya Malaviya, et al.2026
67. Shuttle Between Symbolic Instructions and Neural Parameters of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Wangtao Sun, Haotian Xu, Huanxuan Liao, et al.2026
68. SOP-Maze: Evaluating Large Language Models on Complicated Business Standard Operating ProceduresFindings of the Association for Computational LinguisticsJiaming Wang, Zhe Tang, Zehao Jin, et al.2026
69. Thinking Twice Makes Large Language Models Safer and More HelpfulFindings of the Association for Computational LinguisticsYutao Mou, Yuxiao Luo, Shikun Zhang, et al.2026
70. Tracing the Light of Thought: A Probabilistic Self- and Cross-Consistency Verification Mechanism Improving Mathematical Reasoning in LLMsFindings of the Association for Computational LinguisticsXiaoyang Liu, Dawei Wang, Tian Li, et al.2026
71. We Are What We Repeatedly Do: Improving Long Context Instruction FollowingFindings of the Association for Computational LinguisticsPreston K Robinette, Andrew Hard, Swaroop Ramaswamy, et al.2026

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