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 281–290 of 712 papers

TitleStatusHype
A Framework for Large Scale Synthetic Graph Dataset Generation—0
Fast Contextual Scene Graph Generation With Unbiased Context Augmentation—0
FairWire: Fair Graph Generation—0
Conformal Prediction and MLLM aided Uncertainty Quantification in Scene Graph Generation—0
Evaluating the Cybersecurity Risk of Real World, Machine Learning Production Systems—0
Fairness Amidst Non-IID Graph Data: A Literature Review—0
FairGen: Towards Fair Graph Generation—0
FactReranker: Fact-guided Reranker for Faithful Radiology Report Summarization—0
Computing Steiner Trees using Graph Neural Networks—0
HOIverse: A Synthetic Scene Graph Dataset With Human Object Interactions—0
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Benchmark Results

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