Who cites Jaewook Kang
- Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and BeyondACM Transactions on Knowledge Discovery from DataJingfeng Yang, Hongye Jin, Ruixiang Tang, et al.2023 · 814 citations
- Large Language Models Can Self-ImproveConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaxin Huang, Shixiang Gu, Le Hou, et al.2023 · 575 citations
- 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
- A Survey on Large Language Models for Code GenerationarXiv:2406.00515Juyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 367 citations
- Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
- Want To Reduce Labeling Cost? GPT-3 Can HelpFindings of the Association for Computational LinguisticsShuohang Wang, Yang Liu, Yichong Xu, et al.2021 · 300 citations
- A Holistic Approach to Undesired Content Detection in the Real WorldProceedings of the AAAI Conference on Artificial IntelligenceTodor Markov, Chong Zhang, Sandhini Agarwal, et al.2022 · 263 citations
- Large Language Models for Data Annotation and Synthesis: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Zhen Tan, Dawei Li, Song Wang, et al.2024 · 262 citations
- Synthetic Data Generation with Large Language Models for Text Classification: Potential and LimitationsConference on Empirical Methods in Natural Language Processing (EMNLP)Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu, et al.2023 · 242 citations
- On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A SurveyFindings of the Association for Computational LinguisticsLin Long, Rui Wang, Ruixuan Xiao, et al.2024 · 237 citations
- Generating Training Data with Language Models: Towards Zero-Shot Language UnderstandingarXiv:2202.04538Yu Meng, Jiaxin Huang, Yu Zhang, et al.2022 · 210 citations
- 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
- Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human InterventionsAnnual Meeting of the Association for Computational Linguistics (ACL)John Chung, Ece Kamar, Saleema Amershi2023 · 144 citations
- Data Augmentation for Intent Classification with Off-the-shelf Large Language ModelsWorkshop on Natural Language Processing for Conversational AIGaurav Sahu, Pau Rodriguez, Issam Laradji, et al.2022 · 132 citations
- Ground-Truth Labels Matter: A Deeper Look into Input-Label DemonstrationsConference on Empirical Methods in Natural Language Processing (EMNLP)Kang Min Yoo, Junyeob Kim, Hyuhng Joon Kim, et al.2022 · 114 citations
- OpenStance: Real-world Zero-shot Stance DetectionConference on Computational Natural Language Learning (CoNLL)Hanzi Xu, Slobodan Vucetic, Wenpeng Yin2022 · 32 citations
- LLM-as-a-Judge & Reward Model: What They Can and Cannot DoarXiv:2409.11239Guijin Son, Hyunwoo Ko, Hoyoung Lee, et al.2024 · 27 citations
- Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and EvaluationACM Computing SurveysSteffen Eger, Yong Cao, Jennifer D'Souza, et al.2025 · 25 citations
- Diversity-oriented Data Augmentation with Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zaitian Wang, Jinghan Zhang, Xinhao Zhang, et al.2025 · 17 citations
- 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
- Can LLMs Augment Low-Resource Reading Comprehension Datasets? Opportunities and ChallengesarXiv:2309.12426Vinay Samuel, Houda Aynaou, Arijit Ghosh Chowdhury, et al.2023 · 16 citations
- A Rigorous Evaluation of LLM Data Generation Strategies for Low-Resource LanguagesConference on Empirical Methods in Natural Language Processing (EMNLP)Tatiana Anikina, Jan Cegin, Jakub Simko, et al.2025 · 11 citations
- 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
- 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
- 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
- Better as Generators Than Classifiers: Leveraging LLMs and Synthetic Data for Low-Resource Multilingual ClassificationFindings of the Association for Computational LinguisticsBranislav Pecher, Jan Cegin, Robert Belanec, et al.2026 · 1 citation
- Synthetic Function Demonstrations Improve Generation in Low-Resource Programming LanguagesLanguage Resources and Evaluation Conference (LREC)Nick McKenna, Xinnuo Xu, Jack Williams, et al.2026 · 1 citation
- AnalystBench: Benchmarking professional long-form report generation with web-mined multimodal tasksFindings of the Association for Computational LinguisticsChau Minh Pham, Zichao Wang, Puneet Mathur, et al.2026
- Evaluation Pitfalls and Sparsity Limitations in LLM-based Confidence Estimates for ClassificationFindings of the Association for Computational LinguisticsElena Merdjanovska, Omar Zaidan, Andreas Rücklé2026
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