🧑‍🔬 Who cites Hyunjae Kim

101 citations of their works from 101 papers of our library (of the 149,439 whose bibliographies we read) · 20 with a page here, the most cited first · ← Hyunjae Kim

1. Judging LLM-as-a-Judge with MT-Bench and Chatbot ArenaConference on Neural Information Processing Systems (NeurIPS)Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.2023 · 4,573 citations
2. Leveraging Passage Retrieval with Generative Models for Open Domain Question AnsweringConference of the European Chapter of the Association for Computational Linguistics (EACL)Gautier Izacard, Edouard Grave2021 · 1,692 citations
3. Latent Retrieval for Weakly Supervised Open Domain Question AnsweringAnnual Meeting of the Association for Computational Linguistics (ACL)Kenton Lee, Ming-Wei Chang, Kristina Toutanova2019 · 1,253 citations
4. Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question AnsweringarXiv:1911.10470Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, et al.2019 · 280 citations
5. How Context Affects Language Models' Factual PredictionsarXiv:2005.04611Fabio Petroni, Patrick Lewis, Aleksandra Piktus, et al.2020 · 234 citations
6. AlpaGasus: Training A Better Alpaca with Fewer DataarXiv:2307.08701Lichang Chen, Shiyang Li, Jun Yan, et al.2023 · 220 citations
7. Real-Time Open-Domain Question Answering with Dense-Sparse Phrase IndexAnnual Meeting of the Association for Computational Linguistics (ACL)Minjoon Seo, Jinhyuk Lee, Tom Kwiatkowski, et al.2019 · 218 citations
8. LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation MethodsarXiv:2412.05579Haitao Li, Qian Dong, Junjie Chen, et al.2024 · 195 citations
9. Revealing the Importance of Semantic Retrieval for Machine Reading at ScaleConference on Empirical Methods in Natural Language Processing (EMNLP)Yixin Nie, Songhe Wang, Mohit Bansal2019 · 190 citations
10. From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction TuningarXiv:2308.12032Ming Li, Yong Zhang, Zhitao Li, et al.2023 · 161 citations
11. JudgeLM: Fine-tuned Large Language Models are Scalable JudgesarXiv:2310.17631Lianghui Zhu, Xinggang Wang, Xinlong Wang2023 · 145 citations
12. Benchmarking Large Language Models on Answering and Explaining Challenging Medical QuestionsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Hanjie Chen, Zhouxiang Fang, Yash Singla, et al.2025 · 75 citations
13. Small Language Models Learn Enhanced Reasoning Skills from Medical TextbooksarXiv:2404.00376Hyunjae Kim, Hyeon Hwang, Jiwoo Lee, et al.2024 · 75 citations
14. Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-TuningarXiv:2402.00530Ming Li, Yong Zhang, Shwai He, et al.2024 · 60 citations
15. HeQ: a Large and Diverse Hebrew Reading Comprehension BenchmarkAmir DN Cohen, Hilla Merhav, Yoav Goldberg, et al.2023 · 13 citations
16. EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific DiscoveryarXiv:2603.08127Yougang Lyu, Xi Zhang, Xinhao Yi, et al.2026 · 10 citations
17. Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy ParadigmConference on Empirical Methods in Natural Language Processing (EMNLP)Zhuo Li, Yuhao Du, Xiaoqi Jiao, et al.2025 · 5 citations
18. No Shortcuts to Culture: Indonesian Multi-hop Question Answering for Complex Cultural UnderstandingTransactions of the Association for Computational Linguistics (TACL)Vynska Amalia Permadi, Xingwei Tan, Nafise Sadat Moosavi, et al.2026 · 1 citation
19. Position: Biomedical NLP Demands Specialization, Not GeneralizationWorkshop on Linguistic Analysis for HealthToushik Wasi, Azmine2026
20. Routing with Generated Data: Annotation-Free LLM Skill Estimation and Expert SelectionAnnual Meeting of the Association for Computational Linguistics (ACL)Tianyi Niu, Justin Chen, Genta Indra Winata, et al.2026

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