SOURCE-LINKED INTELLIGENCE
MT-WAM: Reorienting the One-Pass Predictive Representation Toward Action Generation
Fast-WAM shows that video-action co-training improves control without generating future video at inference, making the representation from a single video diffusion Transformer forward central to action generation. However, future-observation prediction does not explicitly prioritize the future dynamics and visual structure needed for control. We present MT-WAM, which retains the original training objectives and adds complementary supervision for future two-dimensional point trajectories and visual features. A lightweight dual-stream branch copied from the video backbone's final blocks provides
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-18T08:23:15.000Z
First collected: 2026-09-23T14:01:59.594Z. This is not the publication date.