ROBOTNESS
上級arXiv

EWAM: Emergent Depth-Wise Specialization in a Unified Embodied Model -- From Semantic Understanding through Visual Foresight to Action

Hao Wang, Jiajun Wen, Jingzhi Liu, Shuoshuo Xue, Zhiliang Chen, Min Lin, Yicheng Chang, Xiaoyu Guo, Yukang Zhuo, Zheng Chong, Yunshuang Nie, Jian Zhang, Weijia Liufu, Qingman Wu, Heming Xu, Bingchang Song, Dantong Wu, Zhiyuan Wang, Hang Xu, Jianhua Han
日本語版は未提供のため、英語原文で表示しています。
要旨より

Vision-language-action (VLA) policies emphasize semantic understanding, whereas world-action models (WAMs) learn predictive representations of environment dynamics. Systems that expose a policy to both sources often still concentrate action computation on a single expert.

要旨より。当社による要約は作成中です。