Seq103: A Unified Neuroevolution Framework for Compact Sequence Architecture Discovery

📰 ArXiv cs.AI

arXiv:2606.07664v1 Announce Type: cross Abstract: Neuroevolution is a representative neural architecture search paradigm that evolves both network topology and weights through evolutionary algorithms. In this paper, we propose Seq103, a unified NEAT-style neuroevolution framework for compact sequence architecture discovery. Seq103 consists of a shared evolutionary backbone and an optional recurrent extension. The shared backbone includes an elementary node-and-connection representation, per-clas

Published 9 Jun 2026
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