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 51–75 of 712 papers

TitleStatusHype
Developing a Scalable Benchmark for Assessing Large Language Models in Knowledge Graph EngineeringCode1
A Simple and Scalable Representation for Graph GenerationCode1
A Graph is Worth K Words: Euclideanizing Graph using Pure TransformerCode1
Fine-Grained Evaluation of Large Vision-Language Models in Autonomous DrivingCode1
Formal Query Building with Query Structure Prediction for Complex Question Answering over Knowledge BaseCode1
Efficient Initial Pose-graph Generation for Global SfMCode1
Efficient Graph Generation with Graph Recurrent Attention NetworksCode1
Efficient and Scalable Graph Generation through Iterative Local ExpansionCode1
EgoExOR: An Ego-Exo-Centric Operating Room Dataset for Surgical Activity UnderstandingCode1
AutoKG: Efficient Automated Knowledge Graph Generation for Language ModelsCode1
CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle TrainingCode1
Advancing Graph Generation through Beta DiffusionCode1
Face Super-Resolution Using Stochastic Differential EquationsCode1
Context-Aware Scene Graph Generation With Seq2Seq TransformersCode1
GSDiff: Synthesizing Vector Floorplans via Geometry-enhanced Structural Graph GenerationCode1
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph GenerationCode1
Data Imputation with Iterative Graph ReconstructionCode1
CARE: Causality Reasoning for Empathetic Responses by Conditional Graph GenerationCode1
Bridging Knowledge Graphs to Generate Scene GraphsCode1
Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph AnalysisCode1
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense ReasoningCode1
Compositional Feature Augmentation for Unbiased Scene Graph GenerationCode1
Biasing Like Human: A Cognitive Bias Framework for Scene Graph GenerationCode1
3M-Diffusion: Latent Multi-Modal Diffusion for Language-Guided Molecular Structure GenerationCode1
CogTree: Cognition Tree Loss for Unbiased Scene Graph GenerationCode1
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Benchmark Results

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