SPARD defends LLMs from harmful fine-tuning attacks via alternating safety projections and relevance-diversity DPP data selection, reporting lowest attack success rates on GSM8K and OpenBookQA while keeping task accuracy.
Targeted vaccine: Safety alignment for large language models against harmful fine-tuning via layer-wise perturbation.IEEE Transactions on Information Forensics and Security, 2025a
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SPARD: Defending Harmful Fine-Tuning Attack via Safety Projection with Relevance-Diversity Data Selection
SPARD defends LLMs from harmful fine-tuning attacks via alternating safety projections and relevance-diversity DPP data selection, reporting lowest attack success rates on GSM8K and OpenBookQA while keeping task accuracy.