SOTAVerified

Graph Generation

Graph Generation is an important research area with significant applications in drug and material designs.

Source: Graph Deconvolutional Generation

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 401–410 of 712 papers

TitleStatusHype
From Easy to Hard: Learning Curricular Shape-aware Features for Robust Panoptic Scene Graph Generation—0
From Graph Generation to Graph Classification—0
From Route Instructions to Landmark Graphs—0
FunGraph: Functionality Aware 3D Scene Graphs for Language-Prompted Scene Interaction—0
G2A2: An Automated Graph Generator with Attributes and Anomalies—0
GEMS: Scene Expansion using Generative Models of Graphs—0
Generalized Unbiased Scene Graph Generation—0
Generalized Visual Relation Detection with Diffusion Models—0
Generating Triples with Adversarial Networks for Scene Graph Construction—0
Generative AI for Visualization: State of the Art and Future Directions—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RNNStreetMover0.03—Unverified
2GraphRNNStreetMover0.02—Unverified
3GGT without CAStreetMover0.02—Unverified
4GGTStreetMover0.02—Unverified