Before revision:  To address this, we propose K-Adapter, which remains the original parameters of the pre-trained model fixed and supports continual knowledge infusion .
After revision:  To address this, we propose K-Adapter, which remains the original parameters of the pre-trained model fixed and supports the development of versatile knowledge-infused model .