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 261–270 of 712 papers

TitleStatusHype
CoPa-SG: Dense Scene Graphs with Parametric and Proto-Relations—0
A Simple Baseline for Weakly-Supervised Scene Graph Generation—0
HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group Activity Scene Graph Generation in Videos—0
Form follows Function: Text-to-Text Conditional Graph Generation based on Functional Requirements—0
Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning—0
Focused Discriminative Training For Streaming CTC-Trained Automatic Speech Recognition Models—0
FLOWGEN: Fast and slow graph generation—0
Continuous Graph Flow—0
Flatten Graphs as Sequences: Transformers are Scalable Graph Generators—0
Contextual Associated Triplet Queries for Panoptic 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