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DexTacWAM: A Visuo-Tactile World-Action Model for Dexterous Manipulation

Paper recorded by Signals 4 on 2026-09-21 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-21 on arXiv · recorded by Signals 4 on 2026-09-22

Category: cs.AI · 人工智能 · first seen 2026-09-22

Abstract

Dexterous manipulation depends on contact dynamics that are often only partially observable from vision. Recent World-Action Models (WAMs) couple predictive video world modeling with action generation, but remain largely vision-centric and therefore cannot directly model these contact dynamics. We present DexTacWAM, a visuo-tactile WAM that encodes each fingertip independently, aggregates the resu

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#3 most recent of 340 cs.AI papers we have recorded · ↑ newer: WorldCrafter: Consistent Video World Model with Implicit 3D-aware Memo · ↓ older: Harness-Zero: Harness Distillation via Agent-as-Harness
Cite this page: DexTacWAM: A Visuo-Tactile World-Action Model for Dexterous Manipulation: the #3 most recent of 340 cs.AI papers we have recorded (as of 2026-09-21). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/dextacwam-a-visuo-tactile-world-action-model-for-dexterous-manipulation.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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