Fine-tuned language models with similar emergent-misalignment rates can exhibit different profiles of misaligned behavior.
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Applying EMERGE to 8 open-weight models and 13 fine-tuning datasets, we find that models with similar broad misalignment rates can exhibit very different behavioural profiles that a single score cannot capture.
Abstract, main empirical finding of the EMERGE benchmark, offered against single-score EM evaluation.
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