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 491–500 of 712 papers

TitleStatusHype
Enhanced Data Transfer Cooperating with Artificial Triplets for Scene Graph Generation—0
Enhancing Large Language Models with Pseudo- and Multisource- Knowledge Graphs for Open-ended Question Answering—0
Ensemble Predicate Decoding for Unbiased Scene Graph Generation—0
ESGNN: Towards Equivariant Scene Graph Neural Network for 3D Scene Understanding—0
Evolving Hard Maximum Cut Instances for Quantum Approximate Optimization Algorithms—0
ExGRG: Explicitly-Generated Relation Graph for Self-Supervised Representation Learning—0
Explainable Artificial Intelligence Recommendation System by Leveraging the Semantics of Adverse Childhood Experiences: Proof-of-Concept Prototype Development—0
Explicit3D: Graph Network with Spatial Inference for Single Image 3D Object Detection—0
Explore Contextual Information for 3D Scene Graph Generation—0
Exploring Context and Visual Pattern of Relationship for 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