What changes after deployment? A survey on On-device Learning in TinyML 事件

What changes after deployment? A survey on On-device Learning in TinyML arXiv:2605.31226v1 Announce Type: cross Abstract: Machine learning models on microcontroller-class devices (TinyML) face a fundamental challenge: post-deployment distribution change undermines static models. On-device learning (ODL) addresses this by running the learning process directly on the device. The existing literature has not characterized how distribution change occurs or how different change types require differen