Reiss Koh

Woosung (Reiss) Koh

Graduate Student

About Me

👋 Hi! I am interested in expanding what is possible for humanity. To this end, I primarily work on Foundation Models and Agents. My work has spanned scaling pre-training, post-training, reasoning, agents, feedback/evaluation, and inference-time scaling. I am currently working on efficient long-context modeling, while remaining broadly interested in high-impact problems. I am perfectly bilingual in English and Korean. If you have similar interests, let’s connect.

Interests

Foundation Models
Reasoning and Agents
Efficient Learning and Models

Education

Graduate Student
KAIST AI
Bachelor's Degree
Yonsei University
Diploma Programme
International Baccalaureate

Publications

[P2] Woosung Koh*, Jeyoung Jeon*, Youngjin Song, Yujin Cheon, Soowon Oh, Jaehyeong Choi, Se-Young Yun. mSFT: Addressing Dataset Mixtures Overfiting Heterogeneously in Multi-task SFT. Pre-print

PDF CODE Post-training Multi-task Generalization

[P1] Woosung Koh*, Sungjun Han*, Segyu Lee, Se-Young Yun, Jay Shin. Generative Visual Code Mobile World Models. Pre-print

PDF CODE PROJECT World Model Mobile GUI Code Generation VLM Post-training

[C4] Woosung Koh, Juyoung Suk, Sungjun Han, Se-Young Yun, Jay Shin. Predicting LLM Reasoning Performance with Small Proxy Model. ICLR 2026

PDF DATASET Pre-training Scaling Reasoning Efficiency

[C3] Woosung Koh, Wonbeen Oh, Jaein Jang, MinHyung Lee, Hyeongjin Kim, Ah Yeon Kim, Joonkee Kim, Junghyun Lee, Taehyeon Kim, Se-Young Yun. AdaSTaR: Adaptive Data Sampling for Training Self-Taught Reasoners. NeurIPS 2025

PDF CODE Post-training Reasoning Data Sampling Training Efficiency

[C2] Woosung Koh*, Jang Han Yoon*, MinHyung Lee, Youngjin Song, Jaegwan Cho, Jaehyun Kang, Taehyeon Kim, Se-Young Yun, Youngjae Yu, Bongshin Lee. C$^2$: Scalable Auto-Feedback for LLM-based Chart Generation. NAACL 2025 Main Long (Oral)

PDF CODE PROJECT VIDEO Chart Generation Code Generation VLM-as-a-Judge Inference-time Scaling

[C1] Woosung Koh, Wonbeen Oh, Siyeol Kim, Suhin Shin, Hyeongjin Kim, Jaein Jang, Junghyun Lee, Se-Young Yun. FlickerFusion: Intra-trajectory Domain Generalizing Multi-Agent RL. ICLR 2025

PDF CODE PROJECT Multi-Agent RL Domain Generalization

[W2] Insu Choi*, Woosung Koh*, Gimin Kang, Yuntae Jang, Woo Chang Kim. Encoding Temporal Statistical-space Priors via Augmented Representation. IJCAI 2024 STRL Workshop (Oral)

PDF Spatio-temporal Prediction Financial Markets

[W1] Woosung Koh*, Insu Choi*, Yuntae Jang*, Gimin Kang, Woo Chang Kim. Curriculum Learning and Imitation Learning for Model-free Control on Financial Time-series. AAAI 2024 AI4TS Workshop (Oral)

PDF Reinforcement Learning Financial Markets

[J1] Insu Choi*, Woosung Koh*, Bonwoo Koo*, Woo Chang Kim. Network-based exploratory data analysis and explainable three-stage deep clustering for financial customer profiling. Engineering Applications of Artificial Intelligence (SCIE, Q1)

PDF Explainable AI Personalized AI