Lee, Yoonjoo

EvalLM: Interactive Evaluation of Large Language Model Prompts on User-Defined Criteria

Kim, T. S., Lee, Y., Shin, J., Kim, Y.-H., & Kim, J. (2023) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 82

Cells, Generators, and Lenses: Design Framework for Object-Oriented Interaction with Large Language Models

Kim, T. S., Lee, Y., Chang, M., & Kim, J. (2023) · Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 56

One vs. Many: Comprehending Accurate Information from Multiple Erroneous and Inconsistent AI Generations

Lee, Y., Son, K., Kim, T. S., Kim, J., Chung, J. J. Y., Adar, E., & Kim, J. (2024) · The 2024 ACM Conference on Fairness, Accountability, and Transparency

Information Retrieval and Search BehaviorTopic Modeling

Cited by 36

DAPIE: Interactive Step-by-Step Explanatory Dialogues to Answer Children’s Why and How Questions

Lee, Y., Kim, T. S., Kim, S., Yun, Y., & Kim, J. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

Speech and dialogue systemsIntelligent Tutoring Systems and Adaptive Learning

Cited by 35

VIVID: Human-AI Collaborative Authoring of Vicarious Dialogues from Lecture Videos

Choi, S., Lee, H., Lee, Y., & Kim, J. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems

Artificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive Learning

Cited by 17

Mind the Blind Spots: A Focus-Level Evaluation Framework for LLM Reviews

Shin, H., Tang, J., Lee, Y., Kim, N., Lim, H., Cho, J. Y., Hong, H., Lee, M., & Kim, J. (2025) · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 5