Kaichao Jiang

Your Classifier Can Do More: Towards Balancing the Gaps in Classification, Robustness, and Generation

Joint Energy-based Models (JEMs) are well known for their ability to unify classification and generation within a single framework. Despite their promising generative and discriminative performance, their robustness remains far inferior to adversarial training (AT), which, conversely, achieves stron