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 381–390 of 712 papers

TitleStatusHype
Using Retriever Augmented Large Language Models for Attack Graph Generation—0
Utilizing Graph Generation for Enhanced Domain Adaptive Object Detection—0
Variational Flow Matching for Graph Generation—0
Discrete Graph Auto-Encoder—0
VersaGNN: a Versatile accelerator for Graph neural networks—0
Visual Relationship Detection using Scene Graphs: A Survey—0
Learning Predicates as Functions to Enable Few-shot Scene Graph Prediction—0
Visual Semantic Information Pursuit: A Survey—0
Visual Traffic Knowledge Graph Generation from Scene Images—0
What can Off-the-Shelves Large Multi-Modal Models do for Dynamic 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