SOTAVerified

Graph Generation

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

Source: Graph Deconvolutional Generation

Papers

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Showing 21–30 of 712 papers

TitleStatusHype
Geometry-Complete Diffusion for 3D Molecule Generation and OptimizationCode2
Graph Condensation: A SurveyCode2
DeFoG: Discrete Flow Matching for Graph GenerationCode2
Boosting Knowledge Graph Generation from Tabular Data with RML ViewsCode2
RelationField: Relate Anything in Radiance FieldsCode2
CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle TrainingCode1
Compositional Feature Augmentation for Unbiased Scene Graph GenerationCode1
Combinatorial Complex Score-based Diffusion Modelling through Stochastic Differential EquationsCode1
Context-Aware Scene Graph Generation With Seq2Seq TransformersCode1
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph GenerationCode1
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Benchmark Results

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