arXiv Computer Vision By Qiwen Gu, Jifan Li, Bingjie Gao, Rui Chen, Jing Tang, Xiangxiang Chu, Junqiao Zhao

The Right Future for Action: Learning Action-Relevant Predictive States in World Action Models

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arXiv Computer Vision
Sep 21

MT-WAM: Reorienting the One-Pass Predictive Representation Toward Action Generation

MT‑WAM enhances the Fast‑WAM framework by adding complementary supervision for future 2‑D point trajectories and visual features while keeping the original training objectives. A lightweight dual‑stream branch and structured attention mask isolate motion‑specific processing, and motion‑stream tokens provide additional dynamics cues to the action expert. During inference, MT‑WAM skips future‑video prediction, using cached video and motion information to achieve higher success rates on LIBERO, LIBERO‑Plus, RoboTwin 2.0 Clean2Rand, and several real‑world tasks.

By Yiguang Yang, Jiankun Peng, Xiaoming Wang, Yiran Zhang, Zhibo Fang