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 326–350 of 712 papers

TitleStatusHype
Importance Weighted Structure Learning for Scene Graph Generation—0
Adversarial Stein Training for Graph Energy Models—0
Learning 4D Panoptic Scene Graph Generation from Rich 2D Visual Scene—0
Image Scene Graph Generation (SGG) Benchmark—0
Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks—0
A Novel Weighted Distance Measure for Multi-Attributed Graph—0
Identification of vortex in unstructured mesh with graph neural networks—0
ICST-DNET: An Interpretable Causal Spatio-Temporal Diffusion Network for Traffic Speed Prediction—0
Hyper-relationship Learning Network for Scene Graph Generation—0
HyperGLM: HyperGraph for Video Scene Graph Generation and Anticipation—0
Context-aware Mixture-of-Experts for Unbiased Scene Graph Generation—0
An Interpretable Model for Scene Graph Generation—0
Improving Molecular Graph Generation with Flow Matching and Optimal Transport—0
Improving Query Graph Generation for Complex Question Answering over Knowledge Base—0
Improving Scene Graph Generation with Superpixel-Based Interaction Learning—0
Predicate Debiasing in Vision-Language Models Integration for Scene Graph Generation Enhancement—0
Indoor and Outdoor 3D Scene Graph Generation via Language-Enabled Spatial Ontologies—0
Efficient Dynamic Attributed Graph Generation—0
Influence Maximization (IM) in Complex Networks with Limited Visibility Using Statistical Methods—0
Informative Scene Graph Generation via Debiasing—0
In-game Residential Home Planning via Visual Context-aware Global Relation Learning—0
ESGNN: Towards Equivariant Scene Graph Neural Network for 3D Scene Understanding—0
Instance-incremental Scene Graph Generation from Real-world Point Clouds via Normalizing Flows—0
Instant Policy: In-Context Imitation Learning via Graph Diffusion—0
Hydra-SGG: Hybrid Relation Assignment for One-stage Scene Graph Generation—0
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Benchmark Results

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