Modular Parameter-Efficient Continual Learning in Vision Transformers: From Domain Shifts to Class Streams

Visual recognition systems deployed over time are increasingly expected to adapt to new domains and new categories while preserving prior knowledge, limiting reliance on raw historical images, and keeping inference cost bounded.