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 201–250 of 712 papers

TitleStatusHype
GraphGT: Machine Learning Datasets for Graph Generation and TransformationCode1
Fast Graph Generation via Spectral DiffusionCode1
Scene Graph Generation by Iterative Message PassingCode1
The general theory of permutation equivarant neural networks and higher order graph variational encodersCode1
Fine-Grained Evaluation of Large Vision-Language Models in Autonomous DrivingCode1
Context-Aware Scene Graph Generation With Seq2Seq TransformersCode1
Dense Relational Image Captioning via Multi-task Triple-Stream NetworksCode1
Gradient-Guided Importance Sampling for Learning Discrete Energy-Based ModelsCode0
GPT4SGG: Synthesizing Scene Graphs from Holistic and Region-specific NarrativesCode0
Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion ModelsCode0
GNN-CNN: An Efficient Hybrid Model of Convolutional and Graph Neural Networks for Text RepresentationCode0
Replica Tree-based Federated Learning using Limited DataCode0
Reinforced Molecular Optimization with Neighborhood-Controlled GrammarsCode0
Addressing the Impact of Localized Training Data in Graph Neural NetworksCode0
Recovering Barabási-Albert Parameters of Graphs through DisentanglementCode0
RBA-GCN: Relational Bilevel Aggregation Graph Convolutional Network for Emotion RecognitionCode0
ReFormer: The Relational Transformer for Image CaptioningCode0
Pre-Training on Dynamic Graph Neural NetworksCode0
AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph GeneratorsCode0
GCAL: Adapting Graph Models to Evolving Domain ShiftsCode0
Pixels to Graphs by Associative EmbeddingCode0
Adaptive Visual Scene Understanding: Incremental Scene Graph GenerationCode0
Pixel-wise Graph Attention Networks for Person Re-identificationCode0
S^2Former-OR: Single-Stage Bi-Modal Transformer for Scene Graph Generation in ORCode0
Optimized Crystallographic Graph Generation for Material ScienceCode0
Non-isomorphic Inter-modality Graph Alignment and Synthesis for Holistic Brain MappingCode0
OG-SGG: Ontology-Guided Scene Graph Generation. A Case Study in Transfer Learning for Telepresence RoboticsCode0
Heuristic Semi-Supervised Learning for Graph Generation Inspired by Electoral CollegeCode0
On-Demand and Lightweight Knowledge Graph Generation -- a Demonstration with DBpediaCode0
NetGAN: Generating Graphs via Random WalksCode0
After All, Only The Last Neuron Matters: Comparing Multi-modal Fusion Functions for Scene Graph GenerationCode0
Narrative-of-Thought: Improving Temporal Reasoning of Large Language Models via Recounted NarrativesCode0
Fine-Grained Scene Graph Generation via Sample-Level Bias PredictionCode0
Natural Language Processing for Music Knowledge DiscoveryCode0
Node Embedding via Word Embedding for Network Community DiscoveryCode0
Fine-Grained is Too Coarse: A Novel Data-Centric Approach for Efficient Scene Graph GenerationCode0
A Framework for Large Scale Synthetic Graph Dataset GenerationCode0
Federated Voxel Scene Graph for Intracranial HemorrhageCode0
Multi-Class and Multi-Task Strategies for Neural Directed Link PredictionCode0
Multi-Label Meta Weighting for Long-Tailed Dynamic Scene Graph GenerationCode0
Connector 0.5: A unified framework for graph representation learningCode0
A Scalable AutoML Approach Based on Graph Neural NetworksCode0
Factorizable Net: An Efficient Subgraph-based Framework for Scene Graph GenerationCode0
MALOnt: An Ontology for Malware Threat IntelligenceCode0
MIDGARD: Self-Consistency Using Minimum Description Length for Structured Commonsense ReasoningCode0
Extend, don’t rebuild: Phrasing conditional graph modification as autoregressive sequence labellingCode0
LTLBench: Towards Benchmarks for Evaluating Temporal Logic Reasoning in Large Language ModelsCode0
SaGess: Sampling Graph Denoising Diffusion Model for Scalable Graph GenerationCode0
Let There Be Order: Rethinking Ordering in Autoregressive Graph GenerationCode0
Balanced Graph Structure Learning for Multivariate Time Series ForecastingCode0
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Benchmark Results

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