{"type":"ScholarlyArticle","title":"Towards an Explainer-agnostic Conversational XAI","authors":[{"name":"Navid Nobani","slug":"navid-nobani","given":"Navid","family":"Nobani","affiliation":""},{"name":"Fabio Mercorio","slug":"fabio-mercorio","given":"Fabio","family":"Mercorio","affiliation":""},{"name":"Mario Mezzanzanica","slug":"mario-mezzanzanica","given":"Mario","family":"Mezzanzanica","affiliation":""}],"abstract":"Explainable Artificial Intelligence (XAI) is gaining interests in both academia and industry, mainly thanks to the proliferation of darker more complex black-box solutions which are replacing their more transparent ancestors. Believing that the overall performance of an XAI system can be augmented by considering the end-user as a human being, we are studying the ways we can improve the explanations by making them more informative and easier to use from one hand, and interactive and customisable from the other hand.","doi":"10.24963/ijcai.2021/686","url":"https://ijcai.org/proceedings/2021/686","pdf":"https://ijcai.org/proceedings/2021/0686.pdf","markdown":"https://ijcai.org/proceedings/2021/686.md","bibtex":"https://ijcai.org/proceedings/2021/bibtex/686","volume":{"slug":"2021","title":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2021","url":"https://ijcai.org/proceedings/2021/","year":2021,"location":"Montreal","dates":"19-27 August 2021","editors":"Prof. Zhi-Hua Zhou","isbn":"978-0-9992411-9-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2021"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":686,"pages":{"first":4909,"last":4910},"keywords":["Humans and AI: Intelligent User Interfaces","AI Ethics, Trust, Fairness: Explainability","Humans and AI: Human-Computer Interaction","Natural Language Processing: Dialogue"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}