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 226–250 of 712 papers

TitleStatusHype
Heuristic Semi-Supervised Learning for Graph Generation Inspired by Electoral CollegeCode0
On-Demand and Lightweight Knowledge Graph Generation -- a Demonstration with DBpediaCode0
Optimized Crystallographic Graph Generation for Material ScienceCode0
Non-isomorphic Inter-modality Graph Alignment and Synthesis for Holistic Brain MappingCode0
Node Embedding via Word Embedding for Network Community DiscoveryCode0
After All, Only The Last Neuron Matters: Comparing Multi-modal Fusion Functions for Scene Graph GenerationCode0
Fine-Grained Scene Graph Generation via Sample-Level Bias PredictionCode0
OG-SGG: Ontology-Guided Scene Graph Generation. A Case Study in Transfer Learning for Telepresence RoboticsCode0
Fine-Grained is Too Coarse: A Novel Data-Centric Approach for Efficient Scene Graph GenerationCode0
Federated Voxel Scene Graph for Intracranial HemorrhageCode0
Narrative-of-Thought: Improving Temporal Reasoning of Large Language Models via Recounted NarrativesCode0
Natural Language Processing for Music Knowledge DiscoveryCode0
Connector 0.5: A unified framework for graph representation learningCode0
Multi-Class and Multi-Task Strategies for Neural Directed Link PredictionCode0
A Scalable AutoML Approach Based on Graph Neural NetworksCode0
Multi-Label Meta Weighting for Long-Tailed Dynamic Scene Graph GenerationCode0
NetGAN: Generating Graphs via Random WalksCode0
Factorizable Net: An Efficient Subgraph-based Framework for Scene Graph GenerationCode0
MIDGARD: Self-Consistency Using Minimum Description Length for Structured Commonsense ReasoningCode0
Extend, don’t rebuild: Phrasing conditional graph modification as autoregressive sequence labellingCode0
Let There Be Order: Rethinking Ordering in Autoregressive Graph GenerationCode0
LinkNet: Relational Embedding for Scene GraphCode0
Exploiting Long-Term Dependencies for Generating Dynamic Scene GraphsCode0
LLM Meets Scene Graph: Can Large Language Models Understand and Generate Scene Graphs? A Benchmark and Empirical StudyCode0
Explanation Graph Generation via Generative Pre-training over Synthetic GraphsCode0
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Benchmark Results

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