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 621–630 of 712 papers

TitleStatusHype
Leveraging Auxiliary Text for Deep Recognition of Unseen Visual Relationships—0
Leveraging LLM for Automated Ontology Extraction and Knowledge Graph Generation—0
Leveraging V2X for Collaborative HD Maps Construction Using Scene Graph Generation—0
LIC-GAN: Language Information Conditioned Graph Generative GAN Model—0
Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space—0
Local-Global Information Interaction Debiasing for Dynamic Scene Graph Generation—0
Logical Bias Learning for Object Relation Prediction—0
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation—0
Make Autoregressive Great Again: Diffusion-Free Graph Generation with Next-Scale Prediction—0
Malware Knowledge Graph Generation—0
Show:102550
← PrevPage 63 of 72Next →

Benchmark Results

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