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The Devil in the Details: Emergent Misalignment, Format and Coherence in Open-Weights LLMs

Dickson, Craig
arXiv (All) · Papers
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artificial-intelligencecomputation-and-languagemachine-learning
Prior work has shown that fine-tuning models on a narrow domain with misaligned data can lead to broad misalignment - a phenomenon termed "emergent misalignment" (Betley et al. 2025). While all tested models were susceptible to emergent misalignment, some models showed more resistance than others. S
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