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Harmful SFT Leaves a Continuous Trace in LLM Checkpoint Updates
Safety auditing of post-trained large language models typically relies on model behavior, requiring model execution and depending on the coverage of available evaluations. This work asks a different question: Do the target behaviors optimized during supervised fine-tuning (SFT) leave readable eviden
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