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Minhwa Lee
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Benchmarking cognitive biases in large language models as evaluators
R Koo, M Lee, V Raheja, JI Park, ZM Kim, D Kang
arXiv preprint arXiv:2309.17012, 2023
312023
Under the surface: Tracking the artifactuality of llm-generated data
D Das, K De Langis, A Martin, J Kim, M Lee, ZM Kim, S Hayati, R Owan, ...
arXiv preprint arXiv:2401.14698, 2024
82024
How Far Can We Extract Diverse Perspectives from Large Language Models?
SA Hayati, M Lee, D Rajagopal, D Kang
arXiv preprint arXiv:2311.09799, 2023
82023
Vision Meets Definitions: Unsupervised Visual Word Sense Disambiguation Incorporating Gloss Information
S Kwon, R Garodia, M Lee, Z Yang, H Yu
Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023
32023
Human-AI Collaborative Taxonomy Construction: A Case Study in Profession-Specific Writing Assistants
M Lee, ZM Kim, VA Khetan, D Kang
arXiv preprint arXiv:2406.18675, 2024
2024
LocalTweets to LocalHealth: A Mental Health Surveillance Framework Based on Twitter Data
V Deshpande, M Lee, Z Yao, Z Zhang, JB Gibbons, H Yu
arXiv preprint arXiv:2402.13452, 2024
2024
How Far Can We Extract Diverse Perspectives from Large Language Models? Criteria-Based Diversity Prompting!
S Anugrah Hayati, M Lee, D Rajagopal, D Kang
arXiv e-prints, arXiv: 2311.09799, 2023
2023
Statistical and Machine Learning Approaches to Depressive Disorders Among Adults in the United States: From Factor Discovery to Prediction Evaluation
M Lee
The College of Wooster, 2021
2021
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