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 201–210 of 712 papers

TitleStatusHype
Generative Modelling of Structurally Constrained GraphsCode1
Fast Graph Generation via Spectral DiffusionCode1
RU-Net: Regularized Unrolling Network for Scene Graph GenerationCode1
Graph Generative Model for Benchmarking Graph Neural NetworksCode1
Fine-Grained Evaluation of Large Vision-Language Models in Autonomous DrivingCode1
Context-Aware Scene Graph Generation With Seq2Seq TransformersCode1
Graph R-CNN for Scene Graph GenerationCode1
Devil's on the Edges: Selective Quad Attention for Scene Graph Generation—0
Automated Graph Generation at Sentence Level for Reading Comprehension Based on Conceptual Graphs—0
Automated Generation of Precedence Graphs in Digital Value Chains for Automotive Production—0
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Benchmark Results

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