🧑‍🔬 Who cites Han Guo

206 citations of their works from 206 papers of our library (of the 149,439 whose bibliographies we read) · 46 with a page here, the most cited first · ← Han Guo

1. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement LearningNatureDeepSeek-AI, Daya Guo, Dejian Yang, et al.2025 · 4,728 citations
2. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
3. Unleashing the potential of prompt engineering for large language modelsarXiv:2310.14735 · Patterns 6(6) 101,260 (2025)Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.2023 · 536 citations
4. Large Language Models as OptimizersarXiv:2309.03409Chengrun Yang, Xuezhi Wang, Yifeng Lu, et al.2023 · 413 citations
5. Automatic Prompt Optimization with “Gradient Descent” and Beam SearchConference on Empirical Methods in Natural Language Processing (EMNLP)Reid Pryzant, Dan Iter, Jerry Li, et al.2023 · 409 citations
6. Demystifying Prompts in Language Models via Perplexity EstimationarXiv:2212.04037Hila Gonen, Srini Iyer, Terra Blevins, et al.2022 · 213 citations
7. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesarXiv:2406.06608Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 189 citations
8. Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context Example Selection and OrderingAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiyong Wu, Yaoxiang Wang, Jiacheng Ye, et al.2022 · 159 citations
9. Fine-Tuning Language Models with Just Forward PassesConference on Neural Information Processing Systems (NeurIPS)Sadhika Malladi, Tianyu Gao, Eshaan Nichani, et al.2023 · 153 citations
10. Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and DiscoveryConference on Neural Information Processing Systems (NeurIPS)Yuxin Wen, Neel Jain, John Kirchenbauer, et al.2023 · 141 citations
11. EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt OptimizersarXiv:2309.08532Qingyan Guo, Rui Wang, Junliang Guo, et al.2023 · 111 citations
12. PaperQA: Retrieval-Augmented Generative Agent for Scientific ResearcharXiv:2312.07559Jakub Lála, Odhran O'Donoghue, Aleksandar Shtedritski, et al.2023 · 109 citations
13. PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt OptimizationarXiv:2310.16427Xinyuan Wang, Chenxi Li, Zhen Wang, et al.2023 · 102 citations
14. Optimizing Instructions and Demonstrations for Multi-Stage Language Model ProgramsConference on Empirical Methods in Natural Language Processing (EMNLP)Krista Opsahl-Ong, Michael J Ryan, Josh Purtell, et al.2024 · 99 citations
15. Language Agents as Optimizable GraphsarXiv:2402.16823Mingchen Zhuge, Wenyi Wang, Louis Kirsch, et al.2024 · 91 citations
16. RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model OutputsAnnual Meeting of the Association for Computational Linguistics (ACL)Afra Feyza Akyurek, Ekin Akyurek, Ashwin Kalyan, et al.2023 · 89 citations
17. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
18. On Prompt-Driven Safeguarding for Large Language ModelsarXiv:2401.18018Chujie Zheng, Fan Yin, Hao Zhou, et al.2024 · 85 citations
19. Rainier: Reinforced Knowledge Introspector for Commonsense Question AnsweringConference on Empirical Methods in Natural Language Processing (EMNLP)Jiacheng Liu, Skyler Hallinan, Ximing Lu, et al.2022 · 82 citations
20. TTRL: Test-Time Reinforcement LearningConference on Neural Information Processing Systems (NeurIPS)Yuxin Zuo, Kaiyan Zhang, Li Sheng, et al.2025 · 76 citations
21. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
22. Explore, Establish, Exploit: Red Teaming Language Models from ScratcharXiv:2306.09442Stephen Casper, Jason Lin, Joe Kwon, et al.2023 · 52 citations
23. Parameter-Efficient Fine-Tuning Design SpacesarXiv:2301.01821Jiaao Chen, Aston Zhang, Xingjian Shi, et al.2023 · 47 citations
24. A Systematic Survey of Automatic Prompt Optimization TechniquesConference on Empirical Methods in Natural Language Processing (EMNLP)Kiran Ramnath, Kang Zhou, Sheng Guan, et al.2025 · 40 citations
25. Knowledge Boundary of Large Language Models: A SurveyAnnual Meeting of the Association for Computational Linguistics (ACL)Moxin Li, Yong Zhao, Wenxuan Zhang, et al.2025 · 30 citations
26. Aristotle: IMO-level Automated Theorem ProvingSuperIntelligence - Robotics - Safety & AlignmentTudor Achim, Alex Best, Alberto Bietti, et al.2025 · 29 citations
27. Joint Prompt Optimization of Stacked LLMs using Variational InferenceConference on Neural Information Processing Systems (NeurIPS)Alessandro Sordoni, Xingdi Yuan, Marc-Alexandre Cote, et al.2023 · 23 citations
28. Rethinking Reflection in Pre-TrainingarXiv:2504.04022Essential AI: Darsh J Shah, Peter Rushton, Somanshu Singla, et al.2025 · 15 citations
29. Training a Scientific Reasoning Model for ChemistryarXiv:2506.17238Siddharth M. Narayanan, James D. Braza, Ryan-Rhys Griffiths, et al.2025 · 15 citations
30. 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
31. AMR-TST: Abstract Meaning Representation-based Text Style TransferKaize Shi, Xueyao Sun, Li He, et al.2023 · 11 citations
32. T-STAR: Truthful Style Transfer using AMR Graph as Intermediate RepresentationAnubhav Jangra, Preksha Nema, Aravindan Raghuveer2022 · 11 citations
33. Self-Instructed Derived Prompt Generation Meets In-Context Learning: Unlocking New Potential of Black-Box LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhuo Li, Yuhao Du, Jinpeng Hu, et al.2025 · 9 citations
34. Making Small Language Models Efficient Reasoners: Intervention, Supervision, ReinforcementarXiv:2505.07961Xuechen Zhang, Zijian Huang, Chenshun Ni, et al.2025 · 6 citations
35. Detecting Training Data of Large Language Models via Expectation MaximizationConference of the European Chapter of the Association for Computational Linguistics (EACL)Gyuwan Kim, Yang Li, Evangelia Spiliopoulou, et al.2026 · 5 citations
36. 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
37. Query Decomposition for RAG: Balancing Exploration-ExploitationConference of the European Chapter of the Association for Computational Linguistics (EACL)Roxana Petcu, Kenton Murray, Daniel Khashabi, et al.2026 · 2 citations
38. Diff4TST: Masked Diffusion Language Model for Text Style TransferAnnual Meeting of the Association for Computational Linguistics (ACL)Xinchen Ma, Gaole He, Yunshi Lan, et al.2026
39. Gradient-Guided Multi-Judge Prompt OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)ChenZhuo Zhao, Xinda Wang, Pu Zhao, et al.2026
40. Joint Optimization of Training Data and Policy in RLHFFindings of the Association for Computational LinguisticsZhuohao Yu, Jiali Zeng, Weizheng Gu, et al.2026
41. Reference Attack: A New Cross-Modal Jailbreaking Attack against Multimodal Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Yulong Wang, Yifei Fu, Jiayi Gao2026
42. Test-Time Training for Zero-Resource Dense Retrieval RerankingWorkshop on Towards Knowledgeable Foundation ModelsShiyan Liu, Yichen Li2026
43. Thesis Proposal: Toward a Human-Centered and Perspective-Aware Framework for Reproducible ML Evaluation and AI AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Deepak Pandita, Christopher M. Homan2026
44. Think Earlier, Not Longer: Prompt Optimization via Reducing Unhealthy ExplorationFindings of the Association for Computational LinguisticsLing-I Wu, Minyu Chen, Jingyang Li, et al.2026
45. To Write or to Automate Linguistic Prompts, That Is the QuestionAnnual Conference of the European Association for Machine Translation (EAMT)Marina Sánchez-Torrón, Daria Akselrod, Jason Rauchwerk2026
46. 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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