The current study focuses on systematically analyzing the recent advances in
the field of Multimodal eXplainable Artificial Intelligence (MXAI). In
particular, the relevant primary prediction tasks and publicly available
datasets are initially described. Subsequently, a structured presentation of
the MXAI methods of the literature is provided, taking into account the
following criteria: a) The number of the involved modalities, b) The stage at
which explanations are produced, and c) The type of the adopted methodology
(i.e. mathematical formalism). Then, the metrics used for MXAI evaluation are
discussed. Finally, a comprehensive analysis of current challenges and future
research directions is provided.Comment: 26 pages, 11 figure