activity
20202026
most citedArgumentation and Machine Learning

3 citations · 7 across the 19 of their papers we have counts for

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21 papers · 1 filter

cs.AI2026

Contrastive Explanations in Quantitative Bipolar Argumentation Frameworks

Xiang Yin, Nico Potyka, Antonio Rago +1

Argumentation frameworks are useful tools for representing and reasoning with information in a variety of settings, e.g. in supplementing AI models as they perform classification t…

cs.AI2026

A Theory of Post-hoc Debate Judgement

Xiang Yin, Adam Dejl, Antonio Rago +2

Debates have recently emerged as a useful methodology for agentic AI to improve performance as well as to aid explainability and user engagement. For example, LLM-empowered agents…

cs.AI2026

Argumentation for Common Ground: Finding Zones of Possible Agreement between Individuals in Conflict

Elisa Cavatorta, Antonio Rago

How can common ground between societies in conflict be identified when citizens' acceptability of peace agreements is shaped by contested narratives? Such acceptability is mediated…

cs.AI2026

Towards an Argumentative Foundation for Evaluative AI

Xiang Yin, Tim Miller, Nico Potyka +2

Evaluative AI (EAI) has been recently proposed as a way to support human decision-making, not by producing a single recommendation, but by presenting competing hypotheses together…

cs.AI2026

Argumentative Human-AI Decision-Making: Toward AI Agents That Reason With Us, Not For Us

Stylianos Loukas Vasileiou, Antonio Rago, Francesca Toni +1

Computational argumentation offers formal frameworks for transparent, verifiable reasoning but has traditionally been limited by its reliance on domain-specific information and ext…

cs.AI2026

From User Preferences to Base Score Extraction Functions in Gradual Argumentation (with Appendix)

Aniol Civit, Antonio Rago, Antonio Andriella +2

Gradual argumentation is a field of symbolic AI which is attracting attention for its ability to support transparent and contestable AI systems. It is considered a useful tool in d…