Inkook Chun — accepted AI-conference papers

2026

TraceGen: World Modeling in 3D Trace Space Enables Learning from Cross-Embodiment Videos

Seungjae Lee, Yoonkyo Jung, Inkook Chun, Yao-Chih Lee, Zikui Cai, Hongjia Huang +5

CVPR 2026

Learning new robot tasks on new platforms and in new scenes from only a handful of demonstrations remains challenging. While videos of other embodiments---humans and different robots---are abundant, differences in embodiment, camera, and environment hinder their direct use. We address the small-data

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2025

Dynamic Test-Time Compute Scaling in Control Policy: Difficulty-Aware Stochastic Interpolant Policy

Inkook Chun, Seungjae Lee, Michael Samuel Albergo, Saining Xie, Eric Vanden-Eijnden

NeurIPS 2025poster

Diffusion- and flow-based policies deliver state-of-the-art performance on long-horizon robotic manipulation and imitation-learning tasks. However, these controllers employ a fixed inference budget at every control step, regardless of task complexity, leading to computational inefficiency for simple…

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