Evolutionary Neural Architecture Search with Dual Contrastive Learning

This article likely presents a novel approach to Neural Architecture Search (NAS), combining evolutionary algorithms with dual contrastive learning. The use of 'dual contrastive learning' suggests an attempt to improve the efficiency or effectiveness of the search process by learning representations that are robust to variations in the data or architecture. The source being ArXiv indicates this is a pre-print, suggesting it's a recent research paper.