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 601–610 of 712 papers

TitleStatusHype
Iterative Scene Graph Generation with Generative Transformers—0
Iterative Zero-Shot LLM Prompting for Knowledge Graph Construction—0
Joint Data and Feature Augmentation for Self-Supervised Representation Learning on Point Clouds—0
Joint Generative Modeling of Scene Graphs and Images via Diffusion Models—0
Joint Modeling of Visual Objects and Relations for Scene Graph Generation—0
Keep it Surprisingly Simple: A Simple First Order Graph Based Parsing Model for Joint Morphosyntactic Parsing in Sanskrit—0
KG4Diagnosis: A Hierarchical Multi-Agent LLM Framework with Knowledge Graph Enhancement for Medical Diagnosis—0
KS-GNNExplainer: Global Model Interpretation Through Instance Explanations On Histopathology images—0
Label Semantic Knowledge Distillation for Unbiased 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