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CASA: local text self-attention for visual fusion

Contribution grade

Efficient vision-language architectures · Human-designed research method or resource

Reference score50,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Added local text-to-text attention within dedicated visual fusion layers, retaining cross-attention-like scaling while narrowing the tested performance gap to full visual-token insertion.

Scientific scope

Added local text-to-text attention within dedicated visual fusion layers, retaining cross-attention-like scaling while narrowing the tested performance gap to full visual-token insertion. Inherits cross-attention and blockwise attention. Efficiency and accuracy comparisons are configuration-dependent; continuous visual updates do not give unbounded visual memory. Original title uses via Self-Attention, unlike the later index title.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Inherits cross-attention and blockwise attention. Efficiency and accuracy comparisons are configuration-dependent; continuous visual updates do not give unbounded visual memory. Original title uses via Self-Attention, unlike the later index title.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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