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Anhui University
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Existing referring detection models fall apart when confronted with the scale variations and complexity of aerial imagery, but a new framework closes the gap.
Forget hand-crafting prompts for each graph component – LR-GMP learns a single, low-rank prompt that works across nodes, edges, and weights, boosting generalization.
A nested Mixture-of-Experts architecture lets neural operators pre-trained on diverse PDEs transfer more effectively to downstream tasks.
