🧑‍🔬 Who cites Donghyun Kwak

108 citations of their works from 105 papers of our library (of the 149,439 whose bibliographies we read) · 30 with a page here, the most cited first · ← Donghyun Kwak

1. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
2. Multitask Prompted Training Enables Zero-Shot Task GeneralizationarXiv:2110.08207Victor Sanh, Albert Webson, Colin Raffel, et al.2021 · 1,612 citations
3. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,287 citations
4. P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and TasksAnnual Meeting of the Association for Computational Linguistics (ACL)Xiao Liu, Kaixuan Ji, Yicheng Fu, et al.2022 · 1,017 citations
5. GPT-NeoX-20B: An Open-Source Autoregressive Language ModelBigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language ModelsSidney Black, Stella Biderman, Eric Hallahan, et al.2022 · 831 citations
6. P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and TasksarXiv:2110.07602Xiao Liu, Kaixuan Ji, Yicheng Fu, et al.2021 · 469 citations
7. A Survey on Large Language Models for Code GenerationACM Transactions on Software Engineering and MethodologyJuyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 367 citations
8. Predictability and Surprise in Large Generative ModelsACM Conference on Fairness, Accountability, and Transparency (FAccT)Deep Ganguli, Danny Hernandez, Liane Lovitt, et al.2022 · 268 citations
9. Generating Training Data with Language Models: Towards Zero-Shot Language UnderstandingarXiv:2202.04538Yu Meng, Jiaxin Huang, Yu Zhang, et al.2022 · 210 citations
10. BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and LanguagesConference on Neural Information Processing Systems (NeurIPS)Junho Myung, Nayeon Lee, Yi Zhou, et al.2024 · 152 citations
11. Personal LLM Agents: Insights and Survey about the Capability, Efficiency and SecurityarXiv:2401.05459Yuanchun Li, Hao Wen, Weijun Wang, et al.2024 · 100 citations
12. Multilingual Large Language Model: A Survey of Resources, Taxonomy and FrontiersarXiv:2404.04925Libo Qin, Qiguang Chen, Yuhang Zhou, et al.2024 · 75 citations
13. What Language Model to Train if You Have One Million GPU Hours?arXiv:2210.15424Teven Le Scao, Thomas Wang, Daniel Hesslow, et al.2022 · 73 citations
14. ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Mingjie Liu, Shizhe Diao, Ximing Lu, et al.2025 · 58 citations
15. HyperCLOVA X Technical ReportarXiv:2404.01954Kang Min Yoo, Jaegeun Han, Sookyo In, et al.2024 · 44 citations
16. A Holistic Assessment of the Carbon Footprint of Noor, a Very Large Arabic Language ModelBigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language ModelsImad Lakim, Ebtesam Almazrouei, Ibrahim Abualhaol, et al.2022 · 30 citations
17. LLM-as-a-Judge & Reward Model: What They Can and Cannot DoarXiv:2409.11239Guijin Son, Hyunwoo Ko, Hoyoung Lee, et al.2024 · 27 citations
18. MultiPragEval: Multilingual Pragmatic Evaluation of Large Language ModelsProceedings of the 2nd GenBench Workshop on Generalisation (Benchmarking) in NLPDojun Park, Jiwoo Lee, Seohyun Park, et al.2024 · 17 citations
19. Pragmatic Competence Evaluation of Large Language Models for the Korean LanguagePacific Asia Conference on Language, Information and Computation (PACLIC)Dojun Park, Jiwoo Lee, Hyeyun Jeong, et al.2024 · 11 citations
20. Cross-lingual Collapse: How Language-Centric Foundation Models Shape Reasoning in Large Language ModelsarXiv:2506.05850Cheonbok Park; Jeonghoon Kim; Joosung Lee; Sanghwan Bae; Jaegul Choo;, Kang Min Yoo2025 · 10 citations
21. HS-STaR: Hierarchical Sampling for Self-Taught Reasoners via Difficulty Estimation and Budget ReallocationConference on Empirical Methods in Natural Language Processing (EMNLP)Feng Xiong, Hongling Xu, Yifei Wang, et al.2025 · 9 citations
22. Writing-RL: Advancing Long-form Writing via Adaptive Curriculum Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Xuanyu Lei, Chenliang Li, Yuning Wu, et al.2026 · 4 citations
23. Do Not Step Into the Same River Twice: Learning to Reason from Trial and ErrorAnnual Meeting of the Association for Computational Linguistics (ACL)Chenming Tang, Hsiu-Yuan Huang, Weijie Liu, et al.2026 · 3 citations
24. Incentivizing In-depth Reasoning over Long Contexts with Process Advantage ShapingFindings of the Association for Computational LinguisticsMiao Peng, Weizhou Shen, Nuo Chen, et al.2026 · 3 citations
25. Prune as You Generate: Online Rollout Pruning for Faster and Better RLVRAnnual Meeting of the Association for Computational Linguistics (ACL)Haobo Xu, Sirui Chen, Ruizhong Qiu, et al.2026 · 2 citations
26. A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and SolutionsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.2026
27. Data Efficient RLVR via Off-Policy Influence GuidanceAnnual Meeting of the Association for Computational Linguistics (ACL)Erle Zhu, Dazhi Jiang, Yuan Wang, et al.2026
28. Learning from Cognition: Enhancing RL Efficiency for LLM Reasoning via Hierarchical Metacognitive Decomposition and RefinementAnnual Meeting of the Association for Computational Linguistics (ACL)Zexu Sun, Yongcheng Zeng, Erxue Min, et al.2026
29. Reinforcing Agentic Search Via Reward Density OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Kun Luo, Hongjin Qian, Zheng Liu, et al.2026
30. The Retrieval Bottleneck: Scaling Laws for Reinforcement Learning in RAGAnnual Meeting of the Association for Computational Linguistics (ACL)Shu Zhou, Jinman Leng, Yufei Song, et al.2026

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