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Distance-Aware Attention and Wall-Distance Expert Routing for Transformer-Based 3D Flow Prediction

arXiv · AI, language, vision and robotics · article · Sep 7, 2026 · UTC

Transformer surrogates for 3D flow prediction compress an industrial mesh into a small set of tokens from which every prediction point reads. Two operations follow: the retrieval step in which a point gathers information from the compressed representation, and the feed-forward layer that transforms what it retrieved. In current backbones both are blind to where the point sits in the flow. We condition both on wall-related physical signals. Distance-aware cross-attention (DA-CA) reshapes each volume query by its wall distance before retrieval, so that a point deep in the boundary layer draws di

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