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 441–450 of 712 papers

TitleStatusHype
CGGM: A conditional graph generation model with adaptive sparsity for node anomaly detection in IoT networks—0
Characterizing Malicious Edges targeting on Graph Neural Networks—0
CLIP-Driven Open-Vocabulary 3D Scene Graph Generation via Cross-Modality Contrastive Learning—0
Clustering based opcode graph generation for malware variant detection—0
Collect and Connect Data Leaves to Feature Concepts: Interactive Graph Generation Toward Well-being—0
Cometh: A continuous-time discrete-state graph diffusion model—0
Commonsense Reasoning for Identifying and Understanding the Implicit Need of Help and Synthesizing Assistive Actions—0
Community Detection Graph Convolutional Network for Overlap-Aware Speaker Diarization—0
Computing Steiner Trees using Graph Neural Networks—0
Conformal Prediction and MLLM aided Uncertainty Quantification in 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