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 11–20 of 712 papers

TitleStatusHype
STAR: A First-Ever Dataset and A Large-Scale Benchmark for Scene Graph Generation in Large-Size Satellite ImageryCode2
REACT: Real-time Efficiency and Accuracy Compromise for Tradeoffs in Scene Graph GenerationCode2
EGTR: Extracting Graph from Transformer for Scene Graph GenerationCode2
From Pixels to Graphs: Open-Vocabulary Scene Graph Generation with Vision-Language ModelsCode2
SGTR+: End-to-end Scene Graph Generation with TransformerCode2
Graph Condensation: A SurveyCode2
Boosting Knowledge Graph Generation from Tabular Data with RML ViewsCode2
Geometry-Complete Diffusion for 3D Molecule Generation and OptimizationCode2
Generative Diffusion Models on Graphs: Methods and ApplicationsCode2
DiGress: Discrete Denoising diffusion for graph generationCode2
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Benchmark Results

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