Author

Y. Kobayashi

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#machine learning Preprint Oct 2026

Evaluation of Active Feature Acquisition Policies with Tabular Foundation Models

Active feature acquisition learns policies that sequentially acquire features to maximize information about a target variable. We study how to learn and evaluate such policies from finite offline data using prior-data fitted networks (PFNs), which are off-the-shelf models that output posterior predictive distributions...

Y. Kobayashi, Divyam Madaan, Shalmali Joshi · 0 citations

Preprint Aug 2026

Positive-Unlabeled Preference Optimization For Chest X-ray Report Generation

This work proposes PU-DPO, a preference optimization framework to prevent omission noise from corrupting the preference signal, and reformulates the objective under a positive-unlabeled (PU) learning framework, treating absent mentions as unlabeled rather than truly negative.

Y. Kobayashi, P. Ramesh, Muhammad Ahmed Chaudhry et al. · 0 citations