🧑‍🔬 Who cites Tengyang Xie

228 citations of their works from 208 papers of our library (of the 149,439 whose bibliographies we read) · 76 with a page here, the most cited first · ← Tengyang Xie

1. Large Language Monkeys: Scaling Inference Compute with Repeated SamplingarXiv:2407.21787Bradley Brown, Jordan Juravsky, Ryan Ehrlich, et al.2024 · 270 citations
2. SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language ModelarXiv:2502.02737Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.2025 · 181 citations
3. 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
4. Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-ExpertsFindings of the Association for Computational LinguisticsHaoxiang Wang, Wei Xiong, Tengyang Xie, et al.2024 · 153 citations
5. Iterative Reasoning Preference OptimizationConference on Neural Information Processing Systems (NeurIPS)Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.2024 · 153 citations
6. Process Reinforcement through Implicit RewardsarXiv:2502.01456Ganqu Cui, Lifan Yuan, Zefan Wang, et al.2025 · 151 citations
7. Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with NothingarXiv:2406.08464Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.2024 · 148 citations
8. Skywork-Reward: Bag of Tricks for Reward Modeling in LLMsarXiv:2410.18451Chris Yuhao Liu, Liang Zeng, Jiacai Liu, et al.2024 · 112 citations
9. RLHF Workflow: From Reward Modeling to Online RLHFarXiv:2405.07863Hanze Dong, Wei Xiong, Bo Pang, et al.2024 · 111 citations
10. Nemotron-4 340B Technical ReportarXiv:2406.11704Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.2024 · 107 citations
11. Disentangling Length from Quality in Direct Preference OptimizationFindings of the Association for Computational LinguisticsRyan Park, Rafael Rafailov, Stefano Ermon, et al.2024 · 105 citations
12. Rewarding Progress: Scaling Automated Process Verifiers for LLM ReasoningarXiv:2410.08146Amrith Setlur, Chirag Nagpal, Adam Fisch, et al.2024 · 93 citations
13. Recursive Introspection: Teaching Language Model Agents How to Self-ImproveConference on Neural Information Processing Systems (NeurIPS)Yuxiao Qu, Tianjun Zhang, Naman Garg, et al.2024 · 75 citations
14. Agent Q: Advanced Reasoning and Learning for Autonomous AI AgentsarXiv:2408.07199Pranav Putta, Edmund Mills, Naman Garg, et al.2024 · 68 citations
15. Inference-Time Scaling for Generalist Reward ModelingarXiv:2504.02495Zijun Liu, Peiyi Wang, Runxin Xu, et al.2025 · 65 citations
16. The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-DeterminismConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Yifan Song, Guoyin Wang, Sujian Li, et al.2025 · 64 citations
17. Free Process Rewards without Process LabelsarXiv:2412.01981Lifan Yuan, Wendi Li, Huayu Chen, et al.2024 · 58 citations
18. HelpSteer2-Preference: Complementing Ratings with PreferencesarXiv:2410.01257Zhilin Wang, Alexander Bukharin, Olivier Delalleau, et al.2024 · 57 citations
19. RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-FoldConference on Neural Information Processing Systems (NeurIPS)Amrith Setlur, Saurabh Garg, Xinyang Geng, et al.2024 · 56 citations
20. Critique-out-Loud Reward ModelsarXiv:2408.11791Zachary Ankner, Mansheej Paul, Brandon Cui, et al.2024 · 52 citations
21. Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference FeedbackConference on Neural Information Processing Systems (NeurIPS)Hamish Ivison, Yizhong Wang, Jiacheng Liu, et al.2024 · 50 citations
22. RM-R1: Reward Modeling as ReasoningarXiv:2505.02387Xiusi Chen, Gaotang Li, Ziqi Wang, et al.2025 · 49 citations
23. The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce HarmConference on Empirical Methods in Natural Language Processing (EMNLP)Aakanksha, Arash Ahmadian, Beyza Ermis, et al.2024 · 49 citations
24. Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI SynergyarXiv:2507.01352Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.2025 · 48 citations
25. Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-ThoughtarXiv:2501.04682Violet Xiang, Charlie Snell, Kanishk Gandhi, et al.2025 · 47 citations
26. EuroLLM-9B: Technical ReportarXiv:2506.04079Pedro Henrique Martins, Joao Alves, Patrick Fernandes, et al.2025 · 45 citations
27. AgentInstruct: Toward Generative Teaching with Agentic FlowsarXiv:2407.03502Arindam Mitra, Luciano Del Corro, Guoqing Zheng, et al.2024 · 42 citations
28. CulturalBench: A Robust, Diverse and Challenging Benchmark for Measuring LMs' Cultural Knowledge Through Human-AI Red-TeamingAnnual Meeting of the Association for Computational Linguistics (ACL)Yu Ying Chiu, Liwei Jiang, Bill Yuchen Lin, et al.2025 · 38 citations
29. AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward ModelingFindings of the Association for Computational LinguisticsZihan Liu, Yang Chen, Mohammad Shoeybi, et al.2025 · 37 citations
30. 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
31. Direct Judgement Preference OptimizationConference on Empirical Methods in Natural Language Processing (EMNLP)PeiFeng Wang, Austin Xu, Yilun Zhou, et al.2025 · 35 citations
32. How to Evaluate Reward Models for RLHFarXiv:2410.14872Evan Frick, Tianle Li, Connor Chen, et al.2024 · 31 citations
33. The Hidden Risks of Large Reasoning Models: A Safety Assessment of R1International Joint Conference on Natural Language Processing (IJCNLP)Kaiwen Zhou, Chengzhi Liu, Xuandong Zhao, et al.2025 · 30 citations
34. RMB: Comprehensively Benchmarking Reward Models in LLM AlignmentarXiv:2410.09893Enyu Zhou, Guodong Zheng, Binghai Wang, et al.2024 · 30 citations
35. TICKing All the Boxes: Generated Checklists Improve LLM Evaluation and GenerationarXiv:2410.03608Jonathan Cook, Tim Rocktaschel, Jakob Foerster, et al.2024 · 29 citations
36. LLM-as-a-Judge & Reward Model: What They Can and Cannot DoarXiv:2409.11239Guijin Son, Hyunwoo Ko, Hoyoung Lee, et al.2024 · 27 citations
37. NaturalReasoning: Reasoning in the Wild with 2.8M Challenging QuestionsConference on Neural Information Processing Systems (NeurIPS)Weizhe Yuan, Jane Yu, Song Jiang, et al.2025 · 26 citations
38. Scaling Test-Time Compute Without Verification or RL is SuboptimalarXiv:2502.12118Amrith Setlur, Nived Rajaraman, Sergey Levine, et al.2025 · 26 citations
39. 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
40. Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-GenerationarXiv:2410.02725Rohin Manvi, Anikait Singh, Stefano Ermon2024 · 22 citations
41. Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in AlignmentTransactions of the Association for Computational Linguistics (TACL)Karel D'Oosterlinck, Winnie Xu, Chris Develder, et al.2025 · 20 citations
42. Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal VerificationAnnual Meeting of the Association for Computational Linguistics (ACL)Chengwu Liu, Ye Yuan, Yichun Yin, et al.2025 · 17 citations
43. Can Large Reasoning Models Self-Train?arXiv:2505.21444Sheikh Shafayat, Fahim Tajwar, Ruslan Salakhutdinov, et al.2025 · 16 citations
44. Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Fangzhi Xu, Qiushi Sun, Kanzhi Cheng, et al.2025 · 15 citations
45. JuStRank: Benchmarking LLM Judges for System RankingAnnual Meeting of the Association for Computational Linguistics (ACL)Ariel Gera, Odellia Boni, Yotam Perlitz, et al.2025 · 15 citations
46. MTSA: Multi-turn Safety Alignment for LLMs through Multi-round Red-teamingAnnual Meeting of the Association for Computational Linguistics (ACL)Weiyang Guo, Jing Li, Wenya Wang, et al.2025 · 14 citations
47. MDCure: A Scalable Pipeline for Multi-Document Instruction-FollowingAnnual Meeting of the Association for Computational Linguistics (ACL)Gabrielle Kaili-May Liu, Bowen Shi, Avi Caciularu, et al.2025 · 11 citations
48. Multi-Attribute Steering of Language Models via Targeted InterventionAnnual Meeting of the Association for Computational Linguistics (ACL)Duy Nguyen, Archiki Prasad, Elias Stengel-Eskin, et al.2025 · 11 citations
49. Progress or Regress? Self-Improvement Reversal in Post-trainingarXiv:2407.05013Ting Wu, Xuefeng Li, Pengfei Liu2024 · 10 citations
50. MetaMetrics: Calibrating Metrics For Generation Tasks Using Human PreferencesarXiv:2410.02381Genta Indra Winata, David Anugraha, Lucky Susanto, et al.2024 · 9 citations
51. Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal UncertaintyFindings of the Association for Computational LinguisticsChao Xue, Yao Wang, Mengqiao Liu, et al.2026 · 8 citations
52. MPO: Multilingual Safety Alignment via Reward Gap OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Weixiang Zhao, Yulin Hu, Yang Deng, et al.2025 · 7 citations
53. mR3: Multilingual Rubric-Agnostic Reward Reasoning ModelsarXiv:2510.01146David Anugraha, Shou-Yi Hung, Zilu Tang, et al.2025 · 5 citations
54. RubricBench: Aligning Model-Generated Rubrics with Human StandardsAnnual Meeting of the Association for Computational Linguistics (ACL)Junyi Zhou, Qiyuan Zhang, Yufei Wang, et al.2026 · 3 citations
55. Tailoring Memory Granularity for Multi-Hop Reasoning over Long ContextsFindings of the Association for Computational LinguisticsPeijun Qing, Xingjian Diao, Chiyu Ma, et al.2026 · 3 citations
56. Graders Should Cheat: Privileged Information Enables Expert-Level Automated EvaluationsConference on Empirical Methods in Natural Language Processing (EMNLP)Jin Peng Zhou, Séb Arnold, Nan Ding, et al.2025 · 3 citations
57. Aligning Large Language Models via Fully Self-Synthetic DataAnnual Meeting of the Association for Computational Linguistics (ACL)Shangjian Yin, Zhepei Wei, Xinyu Zhu, et al.2026 · 2 citations
58. OpenGenAlign: A Preference Dataset and Benchmark for Trustworthy Reward Modeling in Open-Ended, Long-Context GenerationFindings of the Association for Computational LinguisticsHanning Zhang, Juntong Song, Juno Zhu, et al.2026 · 2 citations
59. AMALIA: A Fully Open Large Language Model for European PortugueseInternational Conference on Computational Processing of PortugueseAfonso Simplício, Gonçalo Vinagre, Miguel Moura Ramos, et al.2026 · 1 citation
60. Beyond Compromise: Pareto-Lenient Consensus for Efficient Multi-Preference LLM AlignmentFindings of the Association for Computational LinguisticsRenxuan Tan, Rongpeng Li, Zhifeng Zhao, et al.2026 · 1 citation
61. CoAct: Co-Active LLM Preference Learning with Human-AI SynergyAnnual Meeting of the Association for Computational Linguistics (ACL)Ruiyao Xu, Mihir Parmar, Tiankai Yang, et al.2026 · 1 citation
62. From Individual to Common: An Early Exploration of Consensus in Non-verifiable Data for Balanced Preference OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Shangjian Yin, Zhouxing Shi2026 · 1 citation
63. H3Fusion: Helpful, Harmless, Honest Fusion of Aligned LLMsConference of the European Chapter of the Association for Computational Linguistics (EACL)Selim Furkan Tekin, Fatih Ilhan, Sihao Hu, et al.2026 · 1 citation
64. HARM: Learning Hate-Aware Reward Model for Evaluating Natural Language Explanations of Offensive ContentFindings of the Association for Computational LinguisticsLorenzo Puppi Vecchi, Alceu de Souza Britto Jr, Emerson Cabrera Paraiso, et al.2026 · 1 citation
65. SafeSearch: Do Not Trade Safety for Utility in LLM Search AgentsFindings of the Association for Computational LinguisticsQiusi Zhan, Angeline Budiman-Chan, Abdelrahman Zayed, et al.2026 · 1 citation
66. AdaJudge: Adaptive Multi-Perspective Judging for Reward ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Yongliang Miao, Yangyang Liang, Mengnan Du2026
67. COIG-P: A High-Quality and Large-Scale Chinese Preference Dataset for Alignment with Human ValuesFindings of the Association for Computational LinguisticsSiwei Wu, JinCheng Ren, Xeron Du, et al.2026
68. DynamicFocalPO: Adaptive Focusing Strategy for Preference OptimizationFindings of the Association for Computational LinguisticsShu Zhou, Junan Chen, Rui Ling, et al.2026
69. Generalizable LLM Learning of Graph Synthetic Data with Post-training AlignmentFindings of the Association for Computational LinguisticsYizhuo Zhang, Heng Wang, Shangbin Feng, et al.2026
70. MERIT Feedback Elicits Better Bargaining in LLM NegotiatorsAnnual Meeting of the Association for Computational Linguistics (ACL)Jihwan Oh, Murad Aghazada, Yooju Shin, et al.2026
71. PRISM: Probabilistic Reward Model with Inherent Structural ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Yuhang Zhou, Yixin Cao, Yuchen Ni, et al.2026
72. QuantumQA: Enhancing Scientific Reasoning via Physics-Consistent Dataset and Verification-Aware Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Songxin Qu, Tai-Ping Sun, Yun-Jie Wang, et al.2026
73. ReflectRM: Boosting Generative Reward Models via Self-Reflection within a Unified Judgment FrameworkAnnual Meeting of the Association for Computational Linguistics (ACL)Kai Qin, Liangxin Liu, Yu Liang, et al.2026
74. Revisiting Self-Play Preference Optimization: On the Role of Prompt DifficultyFindings of the Association for Computational LinguisticsYao Xiao, Jung-jae Kim, Roy Ka-Wei Lee, et al.2026
75. Self-Guided Alignment: Adaptive Preference Sensing for Multi-Objective GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Ning Wang, Zhanyang Liu, Taotao Zhou, et al.2026
76. WildReward: Learning Reward Models from In-the-Wild Human InteractionsAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.2026

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