Scaling Novel Graph Generation via Lightweight Structure-Guided Autoregressive Models.

arXiv:2606.04287v2 Announce Type: replace-cross Abstract: Generating realistic and diverse graphs is a key problem in machine learning, with applications in molecular discovery, circuit design, cybersecurity, and beyond. However, current graph generative model