From the 1 of 6 linked papers with an AI index.
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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…
RA-PbRL: Provably Efficient Risk-Aware Preference-Based Reinforcement Learning
Yujie Zhao, Jose Efraim Aguilar Escamill, Weyl Lu +1
Reinforcement Learning from Human Feedback (RLHF) has recently surged in popularity, particularly for aligning large language models and other AI systems with human intentions. At…