11 citations · 39 across the 22 of their papers we have counts for
6 papers · 2 filters
A Methodology for Incompleteness-Tolerant and Modular Gradual Semantics for Argumentative Statement Graphs
Antonio Rago, Stylianos Loukas Vasileiou, Francesca Toni +2
Gradual semantics (GS) have demonstrated great potential in argumentation, in particular for deploying quantitative bipolar argumentation frameworks (QBAFs) in a number of real-wor…
Exploring the Effect of Explanation Content and Format on User Comprehension and Trust in Healthcare
Antonio Rago, Bence Palfi, Purin Sukpanichnant +5
AI-driven tools for healthcare are widely acknowledged as potentially beneficial to health practitioners and patients, e.g. the QCancer regression tool for cancer risk prediction.…
Heterogeneous Graph Neural Networks with Post-hoc Explanations for Multi-modal and Explainable Land Use Inference
Xuehao Zhai, Junqi Jiang, Adam Dejl +4
Urban land use inference is a critically important task that aids in city planning and policy-making. Recently, the increased use of sensor and location technologies has facilitate…
Explaining Arguments' Strength: Unveiling the Role of Attacks and Supports (Technical Report)
Xiang Yin, Potyka Nico, Francesca Toni
Quantitatively explaining the strength of arguments under gradual semantics has recently received increasing attention. Specifically, several works in the literature provide quanti…
Contestable AI needs Computational Argumentation
Francesco Leofante, Hamed Ayoobi, Adam Dejl +10
AI has become pervasive in recent years, but state-of-the-art approaches predominantly neglect the need for AI systems to be contestable. Instead, contestability is advocated by AI…
The Reasons that Agents Act: Intention and Instrumental Goals
Francis Rhys Ward, Matt MacDermott, Francesco Belardinelli +2
Intention is an important and challenging concept in AI. It is important because it underlies many other concepts we care about, such as agency, manipulation, legal responsibility,…