Flatten Graphs as Sequences: Transformers are Scalable Graph Generators

We introduce AUTOGRAPH, a scalable autoregressive model for attributed graph generation using decoder-only transformers. By flattening graphs into random sequences of tokens through a reversible process, AUTOGRAPH enables modeling graphs as sequences without relying on additional node features that are expensive to compute, in contrast to diffusion-based approaches.