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#graph-generation News & Analysis

2 articles tagged with #graph-generation. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles
AINeutralarXiv – CS AI · Mar 35/104
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Mitigating topology biases in Graph Diffusion via Counterfactual Intervention

Researchers have developed FairGDiff, a new AI model that addresses bias issues in graph diffusion models used for generating synthetic network data. The model uses counterfactual intervention to eliminate topology biases related to sensitive attributes like gender and age while maintaining data utility.

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AINeutralarXiv – CS AI · Mar 24/105
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Flowette: Flow Matching with Graphette Priors for Graph Generation

Researchers propose Flowette, a new AI framework for generating graphs with recurring structural patterns using continuous flow matching and graph neural networks. The model introduces 'graphettes' as probabilistic priors to better capture domain-specific structures like molecular patterns, showing improvements in synthetic and small-molecule generation tasks.