Author

Hang Liu

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Review Open access Sep 2026

Foundation-Model-Assisted Reward Design for Reinforcement Learning: A Review of Reward Program Synthesis, Multimodal Feedback, and Trustworthiness

Reward functions determine what reinforcement learning agents ultimately optimize, yet reward design for complex tasks has traditionally relied on extensive domain expertise and iterative engineering. Recent large language models and vision–language foundation models have introduced new mechanisms for interpreting task...

Wei Zhu, Jin-Yin Bai, Rui Tang et al. · Information · 0 citations

#machine learning Preprint Sep 2026

Beyond Reconstruction Error: Analytical and Data-Driven Action Tokenization for Autoregressive Vision-Language-Action Models

Discrete action tokenization is central to autoregressive vision-language-action (VLA) models, yet action representations are often evaluated primarily through reconstruction fidelity. We ask which representation properties actually matter for closed-loop control by comparing fixed analytical, data-driven linear, and n...

Yu-Xin Yang, Gao-Han He, Chang-Xue Guan et al. · 0 citations