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 311–320 of 712 papers

TitleStatusHype
Towards Flexible Visual Relationship Segmentation—0
Using Retriever Augmented Large Language Models for Attack Graph Generation—0
Random Walk Diffusion for Efficient Large-Scale Graph Generation—0
MLC-GCN: Multi-Level Generated Connectome Based GCN for AD Analysis—0
MaterioMiner -- An ontology-based text mining dataset for extraction of process-structure-property entities—0
Voxel Scene Graph for Intracranial HemorrhageCode0
SANGRIA: Surgical Video Scene Graph Optimization for Surgical Workflow Prediction—0
Fine-Grained Scene Graph Generation via Sample-Level Bias PredictionCode0
BCTR: Bidirectional Conditioning Transformer for Scene Graph Generation—0
LaMAGIC: Language-Model-based Topology Generation for Analog Integrated Circuits—0
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Benchmark Results

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