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 281–290 of 712 papers

TitleStatusHype
HyperGLM: HyperGraph for Video Scene Graph Generation and Anticipation—0
Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning—0
TreeFormer: Single-view Plant Skeleton Estimation via Tree-constrained Graph GenerationCode0
Towards Unbiased and Robust Spatio-Temporal Scene Graph Generation and Anticipation—0
Unbiased Scene Graph Generation by Type-Aware Message Passing on Heterogeneous and Dual Graphs—0
Instant Policy: In-Context Imitation Learning via Graph Diffusion—0
Latency Optimization in LEO Satellite Communications with Hybrid Beam Pattern and Interference Control—0
Improving Molecular Graph Generation with Flow Matching and Optimal Transport—0
Federated Voxel Scene Graph for Intracranial HemorrhageCode0
Diffusion Twigs with Loop Guidance for Conditional Graph GenerationCode0
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Benchmark Results

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