Author

A. Lokrantz

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#artificial intelligence Jan 2026

Output Embedding Centering for Stable LLM Pretraining

This paper proposes output embedding centering (OEC) as a new mitigation strategy, and demonstrates that it suppresses output logit divergence and finds that $\mu$-loss is significantly less sensitive to regularization hyperparameter tuning than z-loss.

Felix Stollenwerk, A. Lokrantz, Niclas Hertzberg · arXiv.org · 4 citations

#natural language process... Jul 2026

MultiSynt/MT: Trillion-Token Multi-Parallel Pre-Training Data Translated Across 36 Languages

This work introduces MultiSynt/MT, an open synthetic parallel corpus with approximately 4.8 trillion target-language tokens across 36 languages, produced by translating 100 billion high-quality Nemotron-CC tokens with Tower+ and OPUS-MT/HPLT-MT systems, and releases the corpus to support controlled research on multilin...

Maximilian Idahl, Jörg Tiedemann, S. Pyysalo et al. · arXiv.org · 0 citations