World-Action Models inherit world knowledge from video-generative priors, and channel it into executable control signals through embodied experience. Existing systems, however, are monolithic: the generative backbone, visual representation, architecture, information flow, inference procedure, and training data are tigh...
Yu-Ran Wang, Siqiao Huang, Ming-Lei Li et al.· 38 citations· ⚡4
Token-World is introduced, an action-conditioned world model that compresses VLM features into a compact token state, learns future dynamics in this reduced space, and maps predicted states back to the original policy-facing representation for downstream use.
Chu-Yao Fu, Xiao-Wei Chi, Yu-Han Rui et al.· 0 citations
Embodied Artificial Intelligence (AI) introduces cyber–physical risks because digital failures and attacks can cause physical harm. This survey organizes embodied AI safety through a four-layer reference architecture — comprising the physical interaction, system and middleware, algorithm and decision, and cloud–edge an...
Tuo Feng, Yue Zhang, Shi-Ji Zhou et al.· AI Plus· 0 citations
This work proposes HDR (Hierarchical Denoising for Visual Reasoning), a unified framework that integrates hierarchical latents into causal video generation for multi-step reasoning and introduces a level-stratified multi-step video reasoning benchmark with out-of-distribution cases.
This work organizes the embodied data ecosystem as a pyramidspanning five complementary sources: real-robot data, UMI-style data, egocentric and exocentric data, simulation data, and general vision-language data, and further characterize each source in terms of data quality, diversity, reusability, and physical fidelit...
Yifan Ye, Yankai Fu, Ya-hui Lv et al.· arXiv.org· 4 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
