An Empirical Analysis of Continual Learning for Heterogeneous Medical Visual Question Answering
A systematic evaluation of CL for MedVQA across diverse clinical objectives, including classification, multi-label classification, detection, cell counting, and report generation suggests that existing CL methods struggle to maintain stability-plasticity balance when tasks with different objectives and supervision formats are interleaved.