Author

Stefan Larson

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#machine learning Preprint Sep 2026

Rebalancing Token Importance in Language Models with TF-IDF Weighted Cross-Entropy Loss

An information-weighted cross-entropy loss that rescales token-level contributions using TF-IDF statistics, emphasizing semantically informative tokens while down-weighting ubiquitous ones is presented, offering a lightweight and principled way to mitigate memorization without disrupting standard training dynamics.

Zhi-Jian Li, Stefan Larson, Kevin Leach · 0 citations

Book Open access Aug 2026

Sensitive Data Detection in Documents with LLMs

A systematic evaluation of several proprietary and open-source Large Language Models for sensitive entity extraction from documents and a form-filling pipeline that uses vision-capable LLMs to label form fields, generate realistic synthetic personas, and fill real blank forms, enabling reproducible evaluation across di...

Errita Xu, Stefan Larson, Kevin Leach · Proceedings of the 2026 ACM... · 0 citations