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 581–590 of 712 papers

TitleStatusHype
UniQ: Unified Decoder with Task-specific Queries for Efficient Scene Graph Generation—0
Universal Scene Graph Generation—0
Unsupervised Task Graph Generation from Instructional Video Transcripts—0
Using Retriever Augmented Large Language Models for Attack Graph Generation—0
Utilizing Graph Generation for Enhanced Domain Adaptive Object Detection—0
Variational Flow Matching for Graph Generation—0
Discrete Graph Auto-Encoder—0
VersaGNN: a Versatile accelerator for Graph neural networks—0
Visual Relationship Detection using Scene Graphs: A Survey—0
Learning Predicates as Functions to Enable Few-shot Scene Graph Prediction—0
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Benchmark Results

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