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Erik B. Sudderth

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#machine learning Preprint Sep 2026

TEMPO: Learning Temporal Context for Dynamic Robot Manipulation

TEMPO is proposed, which augments a pretrained VLA with two temporal inputs: a motion summary extracted from a frozen video foundation model to resolve motion ambiguity and a compact proprioceptive history to resolve state aliasing.

Zhen-Yang Feng, Jimin Heo, Erik B. Sudderth et al. · 2 citations · ⚡1

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