Safety alignment for Large Language Models is heavily focused on English with limited multilingual representation, particularly damaging low-resource language performance. Related open training datase
Researchers developed a scalable template-based pipeline to generate multilingual safety datasets, revealing that English-only evaluations misjudge multilingual model safety and that culturally localized training improves alignment across languages.
Safety alignment for Large Language Models is heavily focused on English with limited multilingual representation, particularly damaging low-resource language performance. Related open training datasets are often limited in size or do not follow region-localized harmful topics to broaden the scope of alignment beyond cultures. We propose a scalable template-based augmentation pipeline to produce massive multilingual refusal and benign corpora, extracting safe templates from harmful prompts, translating them and then filling in the slots with culturally authentic entities, both harmful and benign. As a result, we release MSafeTemp, a validated corpus spanning 60 languages useful for…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
How I Aligned Your Model: Scaling Up Multilingual Safety Training with Templates was first seen on Hugging Face · Daily papers on Nov 5, 2026. Since then it has appeared in 14 checks on 2 different days. Its best position was #22 of 30, reached on Nov 5, 19:28 UTC. It dropped off the list after Nov 6, 07:28 UTC.
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Not at the moment. It was last on the list on Nov 6, 07:28 UTC, after 2 days of trending.
#22 on Hugging Face · Daily papers, on Nov 5, 19:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Nov 5, 2026 and has been on the list on 2 days (14 checks) since.