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Zhi-Jian Li

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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