Fine-tuning aligned LLMs compromises safety guardrails even with minimal adversarial examples or benign data, creating new risks not covered by existing inference-time protections.
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Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!
Fine-tuning aligned LLMs compromises safety guardrails even with minimal adversarial examples or benign data, creating new risks not covered by existing inference-time protections.