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Sparse Graph-Guided Mamba is proposed, a lightweight AVSE framework that integrates a sparse heterogeneous graph with a linear-complexity Mamba backbone that explicitly models modality-specific relations through content-adaptive attention and cross-frame audio-visual connections, while Mamba captures long-range temporal context.
Forget static domain priors: the best way to rate AI-generated audio quality depends on *which* aspect of quality you're measuring.
