arXiv Machine Learning June 5, 2026 By David Kacz\'er, Magnus J{\o}rgenv{\aa}g, Clemens Vetter, Esha Afzal, Robin Haselhorst, Lucie Flek, Florian Mai

In-Training Defenses against Emergent Misalignment in Language Models

Read the original on arXiv Machine Learning →

arXiv:2508. 06249v3 Announce Type: replace Abstract: Fine-tuning lets practitioners repurpose aligned large language models (LLMs) for new domains, yet recent work reveals emergent misalignment (EM): Even a small, domain-specific fine-tune can induce harmful behaviors far outside the target domain.

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