AIBullisharXiv – CS AI · 7h ago6/10
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Beyond Model Base Retrieval: Weaving Knowledge to Master Fine-grained Neural Network Design
M-DESIGN, a new retrieval-augmented framework, addresses the inefficiency gap between expensive neural architecture search and suboptimal model retrieval by dynamically leveraging historical evidence from prior tasks to discover near-optimal network modifications. Tested on 67,760 graph neural networks across 22 datasets, the method achieves state-of-the-art performance in 79% of cases under computational constraints.