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 611–620 of 712 papers

TitleStatusHype
Automated Graph Generation at Sentence Level for Reading Comprehension Based on Conceptual Graphs—0
Self-Supervised Real-to-Sim Scene Generation—0
Bridging Scene Understanding and Task Execution with Flexible Simulation Environments—0
Reinforced Molecular Optimization with Neighborhood-Controlled GrammarsCode0
After All, Only The Last Neuron Matters: Comparing Multi-modal Fusion Functions for Scene Graph GenerationCode0
Dual ResGCN for Balanced Scene GraphGeneration—0
Explainable Artificial Intelligence Recommendation System by Leveraging the Semantics of Adverse Childhood Experiences: Proof-of-Concept Prototype Development—0
Accurate polyglot semantic parsing with DAG grammars—0
Keep it Surprisingly Simple: A Simple First Order Graph Based Parsing Model for Joint Morphosyntactic Parsing in Sanskrit—0
Disentangled Dynamic Graph Deep GenerationCode0
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Benchmark Results

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