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 681–690 of 712 papers

TitleStatusHype
Graph Edit NetworksCode0
Weakly-Supervised 3D Scene Graph Generation via Visual-Linguistic Assisted Pseudo-labelingCode0
Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph GenerationCode0
DSGG: Dense Relation Transformer for an End-to-end Scene Graph GenerationCode0
Text2KGBench: A Benchmark for Ontology-Driven Knowledge Graph Generation from TextCode0
GraphEBM: Molecular Graph Generation with Energy-Based ModelsCode0
Scene Graph Modification Based on Natural Language CommandsCode0
Benchmark for Research Theme Classification of Scholarly DocumentsCode0
Graph Convolutional Policy Network for Goal-Directed Molecular Graph GenerationCode0
SCENIR: Visual Semantic Clarity through Unsupervised Scene Graph RetrievalCode0
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Benchmark Results

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