Let There Be Order: Rethinking Ordering in Autoregressive Graph Generation

dc.contributor.authorBu, Jieen
dc.contributor.authorMehrab, Kazi Sajeeden
dc.contributor.authorKarpatne, Anujen
dc.date.accessioned2024-02-27T13:53:52Zen
dc.date.available2024-02-27T13:53:52Zen
dc.date.issued2023en
dc.description.abstractConditional graph generation tasks involve training a model to generate a graph given a set of input conditions. Many previous studies employ autoregressive models to incrementally generate graph components such as nodes and edges. However, as graphs typically lack a natural ordering among their components, converting a graph into a sequence of tokens is not straightforward. While prior works mostly rely on conventional heuristics or graph traversal methods like breadth-first search (BFS) or depth-first search (DFS) to convert graphs to sequences, the impact of ordering on graph generation has largely been unexplored. This paper contributes to this problem by: (1) highlighting the crucial role of ordering in autoregressive graph generation models, (2) proposing a novel theoretical framework that perceives ordering as a dimensionality reduction problem, thereby facilitating a deeper understanding of the relationship between orderings and generated graph accuracy, and (3) introducing "latent sort," a learning-based ordering scheme to perform dimensionality reduction of graph tokens. Our experimental results showcase the effectiveness of latent sort across a wide range of graph generation tasks, encouraging future works to further explore and develop learning-based ordering schemes for autoregressive graph generation.en
dc.description.versionSubmitted versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.orcidKarpatne, Anuj [0000-0003-1647-3534]en
dc.identifier.urihttps://hdl.handle.net/10919/118191en
dc.identifier.volumeabs/2305.15562en
dc.language.isoenen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.titleLet There Be Order: Rethinking Ordering in Autoregressive Graph Generationen
dc.title.serialCoRRen
dc.typeArticleen
dc.type.dcmitypeTexten
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Engineeringen
pubs.organisational-group/Virginia Tech/Engineering/Computer Scienceen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Engineering/COE T&R Facultyen

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