Research
I work on human-centered NLP, multi-agent systems, and the computational analysis of group interaction. On the human side, I build corpora of real teams at work. On the model side, I ask whether cognitive diversity can be created in LLMs, and whether it survives long conversations.
01Publications
TIDES: A Longitudinal Bilingual Dataset for Modeling Multi-Party Social Dynamics
Heechan Lee*, Jeonggyu Kang*, Junho Myung, Jaywoong Jeong, Juho Kim, Joseph Seering
*Equal contribution
12 teams · 104 meetings · 76K+ utterances
02Current Work
2025 — now · CSTL
TIDES & Computational Analysis of Group Interaction
Co-leading TIDES, a longitudinal bilingual corpus for modeling multi-party social dynamics, annotated with speaker roles, developmental stages, and interaction-process categories.
- 12 teams · 104 meetings · 76K+ utterances
- Accepted to COLM 2026 (co-first author)
2025 — now · CSTL
Manufacturing Cognitive Diversity via Internal Model Controls
Can internal model controls manufacture useful cognitive diversity within a single base model? I'm building a systematic falsification record to find out.
- Token-matched baselines and effect-size analysis
2025 — now · CSTL
Diversity Persistence in Multi-Agent Conversation
Does diversity survive extended multi-agent conversation, or do agents inevitably converge?
- Multi-turn debate among stance-seeded agents
03Previous Work
Aug 2024 — Feb 2025 · Samsung Electronics
LLM & RAG System Optimization
Built LLM-enhanced RAG systems at Samsung Electronics' Device Solution Division during a 7-month internship.
- Prompt-Induced Reasoning based Query Decomposition: +28% search quality, -43% zero-hit queries
- Query-Document Relevance Check (DeepSeek-R1-Distill-Qwen-32B): 98.1% score stability
- RAG evaluation system applied to 3,000+ real-world evaluations
- Korean-optimized LLM prompt engineering
2024 — 2025 · KAIST
Computer Vision
Course and research projects in generative models, anomaly detection, and CNN optimization.
- StyleCLIP-based localized image editing in GAN latent space
- Audio anomaly detection for industrial machinery (DCASE Challenge)
- CNN architecture optimization (Stanford CS231n based research)