In this talk, we consider VQA using ASP in a modular neuro- symbolic architecture that comprises both subsymbolic components, based on neural networks, and symbolic reasoning components that use ASP. We discuss explanation finding as a use case, which benefit from the versatility of ASP and the rich landscape of ASP extensions, and briefly touch our ongoing work on exploiting LLMs for VQA.
