HERD: Harness-Evolving Recursive Distillation for Continual Learning
Continual learning requires a model to keep acquiring new skills and knowledge without compromising its existing capabilities. Parametric methods suffer from catastrophic forgetting and loss of plasticity. Non-parametric methods, such as prompts, skills, and harnesses, leverage in-context learning but are limited by context length and lossy plain-text compression. To effectively combine their complementary strengths, we propose HERD (Harness-Evolving Recursive Distillation), a hybrid continual learning framework that learns efficiently in the harness and internalizes experience into cumulative capabilities via distillation. On the harness side, HERD continually refines its skills to captu...
| Authors | Xun Sun, Thanh Thi Nguyen, Thuy-Trang Vu |
|---|---|
| Primary category | cs.CL |
| Published | 22 October 2026 |
| Last updated at source | 22 October 2026 |
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