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
Visually-Prompted Language Model for Fine-Grained Scene Graph Generation in an Open WorldCode1
Taking A Closer Look at Visual Relation: Unbiased Video Scene Graph Generation with Decoupled Label LearningCode0
Decomposed Prototype Learning for Few-Shot Scene Graph Generation—0
SGFormer: Semantic Graph Transformer for Point Cloud-based 3D Scene Graph GenerationCode1
Location-Free Scene Graph GenerationCode1
FactReranker: Fact-guided Reranker for Faithful Radiology Report Summarization—0
Hierarchical Relationships: A New Perspective to Enhance Scene Graph GenerationCode1
Prototype-based Embedding Network for Scene Graph GenerationCode1
RAF: Holistic Compilation for Deep Learning Model TrainingCode1
On Hierarchical Multi-Resolution Graph Generative Models—0
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Benchmark Results

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