Papers by Jina Kim
PhaseMI: A Motivational Interviewing Dataset for Enhancing Phase Progression in LLM-based Counseling (2026.findings-acl)
Copied to clipboard
| Challenge: | Existing MI datasets do not explicitly model structured progression of MI phases, which is essential for effective and goal-oriented counseling. |
| Approach: | They propose a phase-structured MI dataset with a data generation framework that employs therapist, client, and supervisor LLMs to explicitly control phase transitions. |
| Outcome: | The proposed model achieves 12.3% better coverage of MI phases, 37.6% in guiding, and 61.1% in choosing. |
SpaBERT: A Pretrained Language Model from Geographic Data for Geo-Entity Representation (2022.findings-emnlp)
Copied to clipboard
| Challenge: | Named geographic entities are the building blocks of many geographic datasets. |
| Approach: | They propose a spatial language model that provides a general-purpose geo-entity representation based on neighboring entities in geospatial data. |
| Outcome: | The proposed model improves on two downstream tasks, showing significant performance improvement compared with existing models that do not use spatial context. |