# SELFHEAL

SELFHEAL moves the defense ahead of fine-tuning: instead of discarding samples, it uses only the base model's own language judgment to tag instructions, repair grammar and coherence, and rewrite suspicious responses. On Llama-3 it cuts attack success by up to 85% relative to post-hoc defenses while keeping natural accuracy comparable to a model trained on clean data; on Mistral the effect weakens markedly, showing the cleansing depends on the base model's own text understanding.

SELFHEAL moves the defense ahead of fine-tuning: instead of discarding samples, it uses only the base model's own language judgment to tag instructions, repair grammar and coherence, and rewrite suspicious responses. On Llama-3 it cuts attack success by up to 85% relative to post-hoc defenses while keeping natural accuracy comparable to a model trained on clean data; on Mistral the effect weakens markedly, showing the cleansing depends on the base model's own text understanding.