Multilingual Safety Signals Are Multi-Layered: Filtering Safety-Degrading Data for Safer LLMs.

arXiv:2609.22144v1 Announce Type: cross Abstract: Preserving safety alignment during large language models fine-tuning is critical, however, recent studies have demonstrated that even benign fine-tuning data may contain safety-degrading samples that silently u