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 341–350 of 712 papers

TitleStatusHype
Predicate Debiasing in Vision-Language Models Integration for Scene Graph Generation Enhancement—0
Indoor and Outdoor 3D Scene Graph Generation via Language-Enabled Spatial Ontologies—0
Efficient Dynamic Attributed Graph Generation—0
Influence Maximization (IM) in Complex Networks with Limited Visibility Using Statistical Methods—0
Informative Scene Graph Generation via Debiasing—0
In-game Residential Home Planning via Visual Context-aware Global Relation Learning—0
ESGNN: Towards Equivariant Scene Graph Neural Network for 3D Scene Understanding—0
Instance-incremental Scene Graph Generation from Real-world Point Clouds via Normalizing Flows—0
Instant Policy: In-Context Imitation Learning via Graph Diffusion—0
Hydra-SGG: Hybrid Relation Assignment for One-stage 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