Yu-Qi Chi

Revisiting Unknowns: Towards Effective and Efficient Open-Set Active Learning

Open-set active learning (OSAL) aims to identify informative samples for annotation when unlabeled data may contain previously unseen classes--a common challenge in safety-critical and open-world scenarios. Existing approaches typically rely on separately trained open-set detectors, introducing subs