🧑‍🔬 Who cites Daniel Guo

269 citations of their works from 269 papers of our library (of the 149,439 whose bibliographies we read) · 69 with a page here, the most cited first · ← Daniel Guo

1. 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
2. Process Reinforcement through Implicit RewardsarXiv:2502.01456Ganqu Cui, Lifan Yuan, Zefan Wang, et al.2025 · 151 citations
3. Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with NothingarXiv:2406.08464Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.2024 · 148 citations
4. ReFT: Reasoning with Reinforced Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Luong Trung, Xinbo Zhang, Zhanming Jie, et al.2024 · 134 citations
5. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
6. Fanar: An Arabic-Centric Multimodal Generative AI PlatformarXiv:2501.13944Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.2025 · 127 citations
7. ALLaM: Large Language Models for Arabic and EnglisharXiv:2407.15390M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.2024 · 113 citations
8. Orca-Math: Unlocking the potential of SLMs in Grade School MatharXiv:2402.14830Arindam Mitra, Hamed Khanpour, Corby Rosset, et al.2024 · 111 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. Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-ConstraintarXiv:2312.11456Wei Xiong, Hanze Dong, Chenlu Ye, et al.2023 · 100 citations
12. A Survey of Reinforcement Learning from Human FeedbackTransactions on Machine Learning ResearchTimo Kaufmann, Paul Weng, Viktor Bengs, et al.2023 · 92 citations
13. Deep Reinforcement Learning at the Edge of the Statistical PrecipicearXiv:2108.13264Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, et al.2021 · 90 citations
14. Mitigating the Alignment Tax of RLHFConference on Empirical Methods in Natural Language Processing (EMNLP)Yong Lin, Hangyu Lin, Wei Xiong, et al.2024 · 83 citations
15. Smaug: Fixing Failure Modes of Preference Optimisation with DPO-PositivearXiv:2402.13228Arka Pal, Deep Karkhanis, Samuel Dooley, et al.2024 · 82 citations
16. From r to Q*: Your Language Model is Secretly a Q-FunctionarXiv:2404.12358Rafael Rafailov, Joey Hejna, Ryan Park, et al.2024 · 72 citations
17. Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Haoxiang Wang, Yong Lin, Wei Xiong, et al.2024 · 68 citations
18. 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
19. Free Process Rewards without Process LabelsarXiv:2412.01981Lifan Yuan, Wendi Li, Huayu Chen, et al.2024 · 58 citations
20. Generative Reward ModelsarXiv:2410.12832Dakota Mahan, Duy Van Phung, Rafael Rafailov, et al.2024 · 58 citations
21. Pedagogical Alignment of Large Language ModelsFindings of the Association for Computational Linguistics: EMNLP 2024Shashank Sonkar, Kangqi Ni, Sapana Chaudhary, et al.2024 · 54 citations
22. Easy-to-Hard Generalization: Scalable Alignment Beyond Human SupervisionConference on Neural Information Processing Systems (NeurIPS)Zhiqing Sun, Longhui Yu, Yikang Shen, et al.2024 · 51 citations
23. mDPO: Conditional Preference Optimization for Multimodal Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Fei Wang, Wenxuan Zhou, James Y. Huang, et al.2024 · 50 citations
24. 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
25. Direct Nash Optimization: Teaching Language Models to Self-Improve with General PreferencesarXiv:2404.03715Corby Rosset, Ching-An Cheng, Arindam Mitra, et al.2024 · 44 citations
26. Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference OptimizationarXiv:2411.10442Weiyun Wang, Zhe Chen, Wenhai Wang, et al.2024 · 44 citations
27. 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
28. ODIN: Disentangled Reward Mitigates Hacking in RLHFarXiv:2402.07319Lichang Chen, Chen Zhu, Davit Soselia, et al.2024 · 38 citations
29. Self-Refine Instruction-Tuning for Aligning Reasoning in Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Leonardo Ranaldi, Andre Freitas2024 · 35 citations
30. LiPO: Listwise Preference Optimization through Learning-to-RankConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Tianqi Liu, Zhen Qin, Junru Wu, et al.2025 · 31 citations
31. Learning Planning-based Reasoning by Trajectories Collection and Process Reward SynthesizingConference on Empirical Methods in Natural Language Processing (EMNLP)Fangkai Jiao, Chengwei Qin, Zhengyuan Liu, et al.2024 · 31 citations
32. Binary Classifier Optimization for Large Language Model AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Seungjae Jung, Gunsoo Han, Daniel Wontae Nam, et al.2025 · 26 citations
33. Step-Controlled DPO: Leveraging Stepwise Error for Enhanced Mathematical ReasoningarXiv:2407.00782Zimu Lu, Aojun Zhou, Ke Wang, et al.2024 · 23 citations
34. Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-GenerationarXiv:2410.02725Rohin Manvi, Anikait Singh, Stefano Ermon2024 · 22 citations
35. Personality Alignment of Large Language ModelsarXiv:2408.11779Minjun Zhu, Yixuan Weng, Linyi Yang, et al.2024 · 21 citations
36. 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
37. Weak-to-Strong Search: Align Large Language Models via Searching over Small Language ModelsConference on Neural Information Processing Systems (NeurIPS)Zhanhui Zhou, Zhixuan Liu, Jie Liu, et al.2024 · 17 citations
38. Self-Supervised Alignment with Mutual Information: Learning to Follow Principles without Preference LabelsConference on Neural Information Processing Systems (NeurIPS)Jan-Philipp Franken, Eric Zelikman, Rafael Rafailov, et al.2024 · 16 citations
39. Outcome-based Exploration for LLM ReasoningarXiv:2509.06941Yuda Song, Julia Kempe, Remi Munos2025 · 15 citations
40. 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
41. Discovering Preference Optimization Algorithms with and for Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Chris Lu, Samuel Holt, Claudio Fanconi, et al.2024 · 14 citations
42. The N+ Implementation Details of RLHF with PPO: A Case Study on TL;DR SummarizationarXiv:2403.17031Shengyi Huang, Michael Noukhovitch, Arian Hosseini, et al.2024 · 14 citations
43. SaRO: Enhancing LLM Safety through Reasoning-based AlignmentarXiv:2504.09420Yutao Mou, Yuxiao Luo, Shikun Zhang, et al.2025 · 11 citations
44. Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier EngineeringarXiv:2411.11504Xinyan Guan, Yanjiang Liu, Xinyu Lu, et al.2024 · 9 citations
45. Genius: A Generalizable and Purely Unsupervised Self-Training Framework For Advanced ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Fangzhi Xu, Hang Yan, Chang Ma, et al.2025 · 8 citations
46. Selective Preference Optimization via Token-Level Reward Function EstimationConference on Empirical Methods in Natural Language Processing (EMNLP)Kailai Yang, Zhiwei Liu, Qianqian Xie, et al.2025 · 8 citations
47. 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
48. FanarGuard: A Culturally-Aware Moderation Filter for Arabic Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Masoomali Fatehkia, Enes Altinisik, Husrev Taha Sencar2026 · 5 citations
49. 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
50. MedQA-CS: Objective Structured Clinical Examination (OSCE)-Style Benchmark for Evaluating LLM Clinical SkillsConference of the European Chapter of the Association for Computational Linguistics (EACL)Zonghai Yao, Zihao Zhang, Chaolong Tang, et al.2026 · 3 citations
51. Bias Fitting to Mitigate Length Bias of Reward Model in RLHFAnnual Meeting of the Association for Computational Linguistics (ACL)Kangwen Zhao, Jianfeng Cai, Jinhua Zhu, et al.2026 · 2 citations
52. Gained in Translation: Privileged Pairwise Judges Enhance Multilingual ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Lintang Sutawika, Gokul Swamy, Steven Wu, et al.2026 · 2 citations
53. 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
54. Energy Matching based Preference Learning for Diffusion Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Shiv Shankar2026 · 1 citation
55. MEAV: Model Editing with Alignment Vectors for inference time LLM alignment in single and multidomain preference spectrumFindings of the Association for Computational LinguisticsSadat Shahriar, Zheng Qi, Nikolaos Pappas, et al.2026 · 1 citation
56. What Makes LLMs Effective Sequential Recommenders? A Study on Preference Intensity and Temporal ContextAnnual Meeting of the Association for Computational Linguistics (ACL)Zhongyu Ouyang, Qianlong Wen, Chunhui Zhang, et al.2026 · 1 citation
57. Safe at the Margins: A General Approach to Safety Alignment in Low-Resource English Languages — A Singlish Case StudyarXiv:2502.12485Isaac Lim, Shaun Khoo, Roy Ka-Wei Lee, et al.2025 · 1 citation
58. Alignment Tuning for Large Language Models: A Data-Centric Lens on Alignment Data PipelinesFindings of the Association for Computational LinguisticsHwanjun Song2026
59. BiasGRPO: Stabilizing Bias Mitigation in High-Variance Reward Landscapes via Group-Relative Policy OptimizationFindings of the Association for Computational LinguisticsSaket Reddy, Ke Yang, ChengXiang Zhai2026
60. Context-Value-Action Architecture for Value-Driven Large Language Model AgentsFindings of the Association for Computational LinguisticsTianZe Zhang, Sirui Sun, Yuhang Xie, et al.2026
61. DynamicFocalPO: Adaptive Focusing Strategy for Preference OptimizationFindings of the Association for Computational LinguisticsShu Zhou, Junan Chen, Rui Ling, et al.2026
62. Flout at Your Own Risk: LLMs Struggle with Pragmatic Cooperativity Under Epistemic AsymmetryarXiv:2607.11053Hannah VanderHoeven, Abhijnan Nath, Nikhil Krishnaswamy2026
63. From Explicit to Implicit: A Theoretical Framework and Transfer Method for Preference Internalization in Language ModelsTransactions of the Association for Computational Linguistics (TACL)Binrui Wang, Yongping Du, Yu Pei, et al.2026
64. Joint Optimization of Training Data and Policy in RLHFFindings of the Association for Computational LinguisticsZhuohao Yu, Jiali Zeng, Weizheng Gu, et al.2026
65. Pseudo-Likelihood Training for Reasoning Diffusion Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Shiv Shankar2026
66. 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
67. Success and Cost Elicit Convention Formation for Efficient CommunicationAnnual Meeting of the Association for Computational Linguistics (ACL)Saujas Vaduguru, Yilun Hua, Yoav Artzi, et al.2026
68. Thinking Twice Makes Large Language Models Safer and More HelpfulFindings of the Association for Computational LinguisticsYutao Mou, Yuxiao Luo, Shikun Zhang, et al.2026
69. Towards Pedagogically Aligned LLM Tutors for Math Mistake RemediationWorkshop on Innovative Use of NLP for Building Educational Applications (BEA)Kseniia Petukhova, Tien Dat Nguyen, Ekaterina Kochmar2026

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