arXiv AI September 25, 2026 By Shengtao Wen, Yunying Yang, Xiang Chen, Lingbing Guo, Yu Tian, Sheng-Jun Huang

Decoupling Knowledge and Privacy: Post-Task Self-Distillation Replay for LLM Continual Learning

The paper introduces SPARK, a method for privacy‑preserving continual learning that decouples knowledge retention from privacy correction. SPARK freezes the post‑task distribution and then selectively corrects it to reduce the likelihood of sensitive content while maintaining strong performance on current and past tasks. Experiments show that this approach effectively suppresses PII and preserves continual‑learning utility across various settings.

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