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cs.AI2025

Retrieval- and Argumentation-Enhanced Multi-Agent LLMs for Judgmental Forecasting (Extended Version with Supplementary Material)

Deniz Gorur, Antonio Rago, Francesca Toni

Judgmental forecasting is the task of making predictions about future events based on human judgment. This task can be seen as a form of claim verification, where the claim corresp…

cs.AI2025

Argumentatively Coherent Judgmental Forecasting

Deniz Gorur, Antonio Rago, Francesca Toni

Judgmental forecasting employs human opinions to make predictions about future events, rather than exclusively historical data as in quantitative forecasting. When these opinions f…

cs.AI2025

On Gradual Semantics for Assumption-Based Argumentation

Anna Rapberger, Fabrizio Russo, Antonio Rago +1

In computational argumentation, gradual semantics are fine-grained alternatives to extension-based and labelling-based semantics . They ascribe a dialectical strength to (component…

cs.AI2025

Contestability in Quantitative Argumentation

Xiang Yin, Nico Potyka, Antonio Rago +2

Contestable AI requires that AI-driven decisions align with human preferences. While various forms of argumentation have been shown to support contestability, Edge-Weighted Quantit…

cs.AI2025

Free Argumentative Exchanges for Explaining Image Classifiers

Avinash Kori, Antonio Rago, Francesca Toni

Deep learning models are powerful image classifiers but their opacity hinders their trustworthiness. Explanation methods for capturing the reasoning process within these classifier…

cs.AI2024

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…