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 501–510 of 712 papers

TitleStatusHype
Scene Graph Generation for Better Image Captioning?—0
BGT-Net: Bidirectional GRU Transformer Network for Scene Graph Generation—0
Formal Query Building with Query Structure Prediction for Complex Question Answering over Knowledge BaseCode1
Learning to Generate Scene Graph from Natural Language SupervisionCode1
GeneAnnotator: A Semi-automatic Annotation Tool for Visual Scene GraphCode1
roadscene2vec: A Tool for Extracting and Embedding Road Scene-GraphsCode1
Adversarial Stein Training for Graph Energy Models—0
From General to Specific: Informative Scene Graph Generation via Balance AdjustmentCode1
ReGen: Reinforcement Learning for Text and Knowledge Base Generation using Pretrained Language ModelsCode1
Learning of Visual Relations: The Devil is in the Tails—0
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Benchmark Results

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