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The human-centric explainable artificial intelligence (HCXAI) community hasraised the need for framing the explanation process as a conversation betweenhuman and machine. In this position paper, we establish desiderata forMediators, text-based conversational agents which are capable of explaining thebehavior of neural models interactively using natural language. From theperspective of natural language processing (NLP) research, we engineer ablueprint of such a Mediator for the task of sentiment analysis and assess howfar along current research is on the path towards dialogue-based explanations.

Mediators: Conversational Agents Explaining NLP Model Behavior