Yung-Chieh Chan — accepted AI-conference papers

2026

ROSETTA: Constructing Code-Based Reward from Unconstrained Language Preference

Sanjana Srivastava, Kangrui Wang, Yung-Chieh Chan, Tianyuan Dai, Manling Li, Ruohan Zhang +3

ICLR 2026poster

Intelligent embodied agents not only need to accomplish preset tasks, but also learn to align with individual human needs and preferences. Extracting reward signals from human language preferences allows an embodied agent to adapt through reinforcement learning. However, human language preferences a…

Cited by 0 Source ↗code ↗Scholar ↗

2023

On the Feasibility of Cross-Task Transfer with Model-Based Reinforcement Learning

Yifan Xu, Nicklas Hansen, Zirui Wang, Yung-Chieh Chan, Hao Su, Zhuowen Tu

ICLR 2023poster

Reinforcement Learning (RL) algorithms can solve challenging control problems directly from image observations, but they often require millions of environment interactions to do so. Recently, model-based RL algorithms have greatly improved sample-efficiency by concurrently learning an internal model…

Cited by 14 Source ↗PDF ↗code ↗Scholar ↗