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 221–230 of 712 papers

TitleStatusHype
Node Embedding via Word Embedding for Network Community DiscoveryCode0
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
NetGAN: Generating Graphs via Random WalksCode0
On-Demand and Lightweight Knowledge Graph Generation -- a Demonstration with DBpediaCode0
Multi-Class and Multi-Task Strategies for Neural Directed Link PredictionCode0
Multi-Label Meta Weighting for Long-Tailed Dynamic Scene Graph GenerationCode0
Narrative-of-Thought: Improving Temporal Reasoning of Large Language Models via Recounted NarrativesCode0
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
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Benchmark Results

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