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 201–225 of 712 papers

TitleStatusHype
Bridging Knowledge Graphs to Generate Scene GraphsCode1
Efficient Graph Generation with Graph Recurrent Attention NetworksCode1
Knowledge-Embedded Routing Network for Scene Graph GenerationCode1
Graph R-CNN for Scene Graph GenerationCode1
Visual Graphs from Motion (VGfM): Scene understanding with object geometry reasoningCode1
Junction Tree Variational Autoencoder for Molecular Graph GenerationCode1
Scene Graph Generation by Iterative Message PassingCode1
NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation—0
GNN-CNN: An Efficient Hybrid Model of Convolutional and Graph Neural Networks for Text RepresentationCode0
SPADE: Spatial-Aware Denoising Network for Open-vocabulary Panoptic Scene Graph Generation with Long- and Local-range Context Reasoning—0
CoPa-SG: Dense Scene Graphs with Parametric and Proto-Relations—0
CAT-SG: A Large Dynamic Scene Graph Dataset for Fine-Grained Understanding of Cataract Surgery—0
HOIverse: A Synthetic Scene Graph Dataset With Human Object Interactions—0
FreeQ-Graph: Free-form Querying with Semantic Consistent Scene Graph for 3D Scene Understanding—0
Bures-Wasserstein Flow Matching for Graph Generation—0
Representing Time-Continuous Behavior of Cyber-Physical Systems in Knowledge Graphs—0
Out-of-Distribution Graph Models Merging—0
Hi-Dyna Graph: Hierarchical Dynamic Scene Graph for Robotic Autonomy in Human-Centric Environments—0
Studying and Improving Graph Neural Network-based Motif Estimation—0
A Reverse Causal Framework to Mitigate Spurious Correlations for Debiasing Scene Graph Generation—0
Graph Guided Diffusion: Unified Guidance for Conditional Graph Generation—0
From Data to Modeling: Fully Open-vocabulary Scene Graph Generation—0
LLM Meets Scene Graph: Can Large Language Models Understand and Generate Scene Graphs? A Benchmark and Empirical StudyCode0
GCAL: Adapting Graph Models to Evolving Domain ShiftsCode0
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