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 41–50 of 712 papers

TitleStatusHype
Adaptive Graph Convolutional Recurrent Network for Traffic ForecastingCode1
Any-Property-Conditional Molecule Generation with Self-Criticism using Spanning TreesCode1
Developing a Scalable Benchmark for Assessing Large Language Models in Knowledge Graph EngineeringCode1
Diffusion-based Graph Generative MethodsCode1
Data Imputation with Iterative Graph ReconstructionCode1
Are scene graphs good enough to improve Image Captioning?Code1
CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle TrainingCode1
A Review and Efficient Implementation of Scene Graph Generation MetricsCode1
A Simple and Scalable Representation for Graph GenerationCode1
Context-Aware Scene Graph Generation With Seq2Seq TransformersCode1
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Benchmark Results

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