4 papers · 1 filter
Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction
Xinyi Li, Zaishuo Xia, Chenjie Hao +1
World models are expected to support imagination over extended temporal horizons, yet most are still trained through local few-step prediction objectives and deployed by recursivel…
Deep Networks Favor Simple Data
Weyl Lu, Chenjie Hao, Yubei Chen
Estimated density is often interpreted as indicating how typical a sample is under a model. Yet deep models trained on one dataset can assign higher density to simpler out-of-distr…
SmallWorlds: Assessing Dynamics Understanding of World Models in Isolated Environments
Xinyi Li, Zaishuo Xia, Weyl Lu +2
Current world models lack a unified and controlled setting for systematic evaluation, making it difficult to assess whether they truly capture the underlying rules that govern envi…
Neural Motion Simulator: Pushing the Limit of World Models in Reinforcement Learning
Chenjie Hao, Weyl Lu, Yifan Xu +1
An embodied system must not only model the patterns of the external world but also understand its own motion dynamics. A motion dynamic model is essential for efficient skill acqui…