Author

Bernardo Modenesi

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#artificial intelligence Preprint Aug 2026

Generalized Graph Variational Autoencoders: Bounded Divergences Control Posterior Collapse

The variational graph autoencoder (VGAE) regularizes its posterior toward the prior with the Kullback-Leibler divergence, a choice inherited from the variational autoencoder rather than argued for. We introduce the generalized graph variational autoencoder (GGVA), which replaces that term with any member of the R\'enyi...

Kleyton da Costa, Bernardo Modenesi, I. Menezes et al. · 0 citations

Preprint Aug 2026

When Should Graph Attention Be Sparse? Learning a Per-Edge Tsallis Index

Graph attention normalizes neighborhood scores with softmax, the maximum-entropy choice under Shannon statistics. But homophilic and heterophilic graphs want different attention shapes, and one fixed normalization cannot serve both. We propose \textbf{LTGA} (\textbf{L}earnable \textbf{T}sallis \textbf{G}raph \textbf{A}...

Kleyton da Costa, Bernardo Modenesi · 0 citations

Preprint Aug 2026

Prompting is not enough: supervised baselines and leakage control for measuring shared decision-making with LLMs in pediatric encounters

Objectives: To determine whether zero-shot prompting of a large language model (LLM) is sufficient to detect shared decision-making (SDM) behaviors in real clinical encounters, and whether supervised learning adds value under patient-grouped, nested evaluation. Methods: We analyzed 21 audio-recorded outpatient surgical...

Bernardo Modenesi, Jody L. Lin, Kimberly A. Kaphingst et al. · 0 citations