World action models improve robotic manipulation by conditioning actions on predicted futures, yet existing tactile variants largely inherit video-generation pipelines that reconstruct future tactile observations through iterative denoising. Such prediction can become unreliable under deployment drift: small changes in...
En-Yi Wang, Ming-Xin Wang, Quan Shi et al.· 0 citations
Learning to predict how the world evolves can provide vision-language-action (VLA) policies with predictive context for long-horizon control, but its effectiveness depends on what future representation is modeled and how it conditions action generation. We introduce PLaW-VLA, which models task-relevant future states in...
Yu Liu, He-Tian Guo, Tianlv Huang et al.· 0 citations
Joint embedding predictive architectures offer a compelling alternative to pixel space reconstruction for visual self-supervised learning, especially in video. Existing video joint embedding predictive architecture methods primarily emphasize one-way masked prediction, where the model predicts masked target representat...
Fei-Wang Yan, Cheng-Yu Miao, Zhi-Yi Yao et al.· 2026 IEEE International Conf...· 0 citations
SeMoCo, a semantic-first motion codec, is introduced together with a dual-axis motion generator for language-conditioned motion generation and $\Omega$-MotionVerse, a large-scale, multi-source human-motion dataset unified under the SOMA representation is constructed.
Tianlv Huang, He-Tian Guo, Zi-Yi Cai et al.· 1 citation
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