Adaptive XAI: Advancing Intelligent Interfaces for Tailored AI Explanations (2nd Edition)

As artificial intelligence becomes increasingly embedded in daily decision-making processes, the need for effective communication between humans and AI systems grows more crucial. The Adaptive XAI (AXAI) workshop, now in its second edition, focuses on developing intelligent interfaces that can adaptively explain AI’s decision-making processes. Building on the success of our inaugural event at IUI 2024, this workshop continues to explore the intersection of Explainable AI and adaptive user interfaces, emphasizing the development of interfaces that dynamically adapt to create explanations that resonate with diverse users. In line with the human-centric principles of the Future Artificial Intelligence Research (FAIR) project, we examine how emerging technologies such as conversational agents and Large Language Models can enhance AI explainability while ensuring explanations remain malleable and responsive to users’ evolving cognitive states and contextual needs.

Authors

Institutions

Publication Details

Published
2025-03-18
DOI
https://doi.org/10.1145/3708557.3716159
Citations
2
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
4.96
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Adaptive XAI: Advancing Intelligent Interfaces for Tailored AI Explanations (2nd Edition)

Tommaso Turchi, Simone Borsci, Andrew Fish, Fabio Paternò et al.
2 citations
Explainable Artificial Intelligence (XAI)
4.96
article

Adaptive XAI: Advancing Intelligent Interfaces for Tailored AI Explanations (2nd Edition)

Tommaso Turchi, Simone Borsci, Andrew Fish, Fabio Paternò, Alessio Malizia, Alan Chamberlain
article en
2 citations

Abstract

As artificial intelligence becomes increasingly embedded in daily decision-making processes, the need for effective communication between humans and AI systems grows more crucial. The Adaptive XAI (AXAI) workshop, now in its second edition, focuses on developing intelligent interfaces that can adaptively explain AI’s decision-making processes. Building on the success of our inaugural event at IUI 2024, this workshop continues to explore the intersection of Explainable AI and adaptive user interfaces, emphasizing the development of interfaces that dynamically adapt to create explanations that resonate with diverse users. In line with the human-centric principles of the Future Artificial Intelligence Research (FAIR) project, we examine how emerging technologies such as conversational agents and Large Language Models can enhance AI explainability while ensuring explanations remain malleable and responsive to users’ evolving cognitive states and contextual needs.

University of Pisa (IT), Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" (IT), University of Nottingham (GB), University of Liverpool (GB), Molde University College (NO), University of Twente (NL)
Openalex Percentile: Top 6%
Explainable Artificial Intelligence (XAI)
4.96
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.