activity
20202026
most citedLLM-TA: An LLM-Enhanced Thematic Analysis Pipeline for Transcripts from Parents of Children with Congenital Heart Disease

3 citations · 4 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CL2026

Identifying Effective Strategies in Prompt Evolution for Stress and Emotion Prediction

SeungHyun Yi, Seungjun Yi, Sriram Sattiraju +12

Early stress detection and risk prediction are crucial for timely mental health assessment and support. While large language models have recently shown promise for social media str…

cs.CL2026

Automated Thematic Analysis for Clinical Qualitative Data: Iterative Codebook Refinement with Full Provenance

Seungjun Yi, Joakim Nguyen, Huimin Xu +9

Thematic analysis (TA) is widely used in health research to extract patterns from patient interviews, yet manual TA faces challenges in scalability and reproducibility. LLM-based a…

cs.CL2025

Position: Thematic Analysis of Unstructured Clinical Transcripts with Large Language Models

Seungjun Yi, Joakim Nguyen, Terence Lim +8

This position paper examines how large language models (LLMs) can support thematic analysis of unstructured clinical transcripts, a widely used but resource-intensive method for un…

cs.CL2025

SFT-TA: Supervised Fine-Tuned Agents in Multi-Agent LLMs for Automated Inductive Thematic Analysis

Seungjun Yi, Joakim Nguyen, Huimin Xu +8

Thematic Analysis (TA) is a widely used qualitative method that provides a structured yet flexible framework for identifying and reporting patterns in clinical interview transcript…

cs.CL2025

Auto-TA: Towards Scalable Automated Thematic Analysis (TA) via Multi-Agent Large Language Models with Reinforcement Learning

Seungjun Yi, Joakim Nguyen, Huimin Xu +4

Congenital heart disease (CHD) presents complex, lifelong challenges often underrepresented in traditional clinical metrics. While unstructured narratives offer rich insights into…

cs.HC2025

TAMA: A Human-AI Collaborative Thematic Analysis Framework Using Multi-Agent LLMs for Clinical Interviews

Huimin Xu, Seungjun Yi, Terence Lim +9

Thematic analysis (TA) is a widely used qualitative approach for uncovering latent meanings in unstructured text data. TA provides valuable insights in healthcare but is resource-i…

cs.CL2025★ 3 cited

LLM-TA: An LLM-Enhanced Thematic Analysis Pipeline for Transcripts from Parents of Children with Congenital Heart Disease

Muhammad Zain Raza, Jiawei Xu, Terence Lim +4

Thematic Analysis (TA) is a fundamental method in healthcare research for analyzing transcript data, but it is resource-intensive and difficult to scale for large, complex datasets…

cs.AI2020★ 1 cited

Improving Multi-Agent Cooperation using Theory of Mind

Terence X. Lim, Sidney Tio, Desmond C. Ong

Recent advances in Artificial Intelligence have produced agents that can beat human world champions at games like Go, Starcraft, and Dota2. However, most of these models do not see…