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
Boosting Knowledge Graph Generation from Tabular Data with RML ViewsCode2
Graph Condensation: A SurveyCode2
MM-OR: A Large Multimodal Operating Room Dataset for Semantic Understanding of High-Intensity Surgical EnvironmentsCode2
Open World Scene Graph Generation using Vision Language ModelsCode2
FastFlows: Flow-Based Models for Molecular Graph GenerationCode2
DiffGraph: Heterogeneous Graph Diffusion ModelCode2
DiscoSG: Towards Discourse-Level Text Scene Graph Parsing through Iterative Graph RefinementCode2
LLM-Based Multi-Agent Systems are Scalable Graph Generative ModelsCode2
Geometry-Complete Diffusion for 3D Molecule Generation and OptimizationCode2
RelTR: Relation Transformer for Scene Graph GenerationCode2
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Benchmark Results

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