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 131–140 of 712 papers

TitleStatusHype
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
Semantic Diversity-aware Prototype-based Learning for Unbiased Scene Graph GenerationCode1
LaMAGIC: Language-Model-based Topology Generation for Analog Integrated Circuits—0
OpenPSG: Open-set Panoptic Scene Graph Generation via Large Multimodal ModelsCode1
A Fair Ranking and New Model for Panoptic Scene Graph GenerationCode1
Any-Property-Conditional Molecule Generation with Self-Criticism using Spanning TreesCode1
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Benchmark Results

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