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 181–190 of 712 papers

TitleStatusHype
CogTree: Cognition Tree Loss for Unbiased Scene Graph GenerationCode1
Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph AnalysisCode1
A Fair Ranking and New Model for Panoptic Scene Graph GenerationCode1
Fine-Grained Scene Graph Generation with Data TransferCode1
Combinatorial Complex Score-based Diffusion Modelling through Stochastic Differential EquationsCode1
OED: Towards One-stage End-to-End Dynamic Scene Graph GenerationCode1
Are scene graphs good enough to improve Image Captioning?Code1
Knowledge Graph Generation From TextCode1
Exploring the Individuality and Collectivity of Intents behind Interactions for Graph Collaborative FilteringCode1
Pard: Permutation-Invariant Autoregressive Diffusion for Graph GenerationCode1
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Benchmark Results

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