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 126–150 of 712 papers

TitleStatusHype
Instruction-Based Molecular Graph Generation with Unified Text-Graph Diffusion ModelCode0
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
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
From Easy to Hard: Learning Curricular Shape-aware Features for Robust Panoptic Scene Graph Generation—0
3D Vessel Graph Generation Using Denoising DiffusionCode1
LTLBench: Towards Benchmarks for Evaluating Temporal Logic Reasoning in Large Language ModelsCode0
The Complexity of Symmetry Breaking Beyond Lex-Leader—0
ESGNN: Towards Equivariant Scene Graph Neural Network for 3D Scene Understanding—0
MissionGNN: Hierarchical Multimodal GNN-based Weakly Supervised Video Anomaly Recognition with Mission-Specific Knowledge Graph Generation—0
Enhanced Data Transfer Cooperating with Artificial Triplets for Scene Graph Generation—0
Cascading Large Language Models for Salient Event Graph GenerationCode0
Generative Modelling of Structurally Constrained GraphsCode1
SE-VGAE: Unsupervised Disentangled Representation Learning for Interpretable Architectural Layout Design Graph GenerationCode0
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Benchmark Results

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