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 321–330 of 712 papers

TitleStatusHype
Fine-Grained is Too Coarse: A Novel Data-Centric Approach for Efficient Scene Graph GenerationCode0
Graph Generation with K^2-treesCode1
A Diffusion Model for Event Skeleton GenerationCode0
Let There Be Order: Rethinking Ordering in Autoregressive Graph GenerationCode0
Building Transportation Foundation Model via Generative Graph Transformer—0
Boosting Knowledge Graph Generation from Tabular Data with RML ViewsCode2
Learning Joint 2D & 3D Diffusion Models for Complete Molecule GenerationCode1
PiVe: Prompting with Iterative Verification Improving Graph-based Generative Capability of LLMsCode1
Brain Imaging-to-Graph Generation using Adversarial Hierarchical Diffusion Models for MCI Causality Analysis—0
MolHF: A Hierarchical Normalizing Flow for Molecular Graph GenerationCode1
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Benchmark Results

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