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We propose a large language model explainability technique for obtaining faithful natural language explanations by grounding the explanations in a reasoning process. When converted to a sequence of tokens, the outputs of the reasoning…

Machine Learning · Computer Science 2026-03-17 Vojtech Cahlik , Rodrigo Alves , Pavel Kordik

Realizability for knowledge representation formalisms studies the following question: given a semantics and a set of interpretations, is there a knowledge base whose semantics coincides exactly with the given interpretation set? We…

Artificial Intelligence · Computer Science 2016-04-01 Thomas Linsbichler , Jörg Pührer , Hannes Strass

The notion of stability in a structured argumentation setup characterizes situations where the acceptance status associated with a given literal will not be impacted by any future evolution of this setup. In this paper, we abstract away…

Artificial Intelligence · Computer Science 2020-12-24 Jean-Guy Mailly , Julien Rossit

Assumption-based Argumentation (ABA) is a well-established form of structured argumentation. ABA frameworks with an underlying atomic language are widely studied, but their applicability is limited by a representational restriction to…

Artificial Intelligence · Computer Science 2026-04-14 Emanuele De Angelis , Fabio Fioravanti , Maria Chiara Meo , Alberto Pettorossi , Maurizio Proietti , Francesca Toni

In this paper we introduce a novel semantics, called defense semantics, for Dung's abstract argumentation frameworks in terms of a notion of (partial) defence, which is a triple encoding that one argument is (partially) defended by another…

Artificial Intelligence · Computer Science 2023-11-23 Beishui Liao , Leendert van der Torre

Argumentation is based on the exchange and valuation of interacting arguments, followed by the selection of the most acceptable of them (for example, in order to take a decision, to make a choice). Starting from the framework proposed by…

Artificial Intelligence · Computer Science 2011-07-04 C. Cayrol , M. C. Lagasquie-Schiex

Recently, Strength-based Argumentation Frameworks (StrAFs) have been proposed to model situations where some quantitative strength is associated with arguments. In this setting, the notion of accrual corresponds to sets of arguments that…

Artificial Intelligence · Computer Science 2022-07-07 Yohann Bacquey , Jean-Guy Mailly , Pavlos Moraitis , Julien Rossit

In this paper, we introduce a new family of argument-ranking semantics which can be seen as a refinement of the classification of arguments into skeptically accepted, credulously accepted and rejected. To this end we use so-called social…

Artificial Intelligence · Computer Science 2024-12-19 Lars Bengel , Giovanni Buraglio , Jan Maly , Kenneth Skiba

Several formal systems, such as resolution and minimal model semantics, provide a framework for logic programming. In this paper, we will survey the use of structural proof theory as an alternative foundation. Researchers have been using…

Logic in Computer Science · Computer Science 2021-11-02 Dale Miller

Dung's abstract argumentation frameworks model acceptability solely in terms of an attack relation, thereby conflating two conceptually distinct aspects of argumentative reasoning: direct conflict between arguments and the structural…

Artificial Intelligence · Computer Science 2026-04-14 Beishui Liao

To resolve conflicts among norms, various nonmonotonic formalisms can be used to perform prioritized normative reasoning. Meanwhile, formal argumentation provides a way to represent nonmonotonic logics. In this paper, we propose a…

Artificial Intelligence · Computer Science 2018-03-06 Beishui Liao , Nir Oren , Leendert van der Torre , Serena Villata

The problem of explaining inconsistency-tolerant reasoning in knowledge bases (KBs) is a prominent topic in Artificial Intelligence (AI). While there is some work on this problem, the explanations provided by existing approaches often lack…

Artificial Intelligence · Computer Science 2025-02-18 Loan Ho , Stefan Schlobach

Evaluating explanations of image classifiers regarding ground truth, e.g. segmentation masks defined by human perception, primarily evaluates the quality of the models under consideration rather than the explanation methods themselves.…

Computer Vision and Pattern Recognition · Computer Science 2023-11-09 Hubert Baniecki , Maciej Chrabaszcz , Andreas Holzinger , Bastian Pfeifer , Anna Saranti , Przemyslaw Biecek

In this paper we propose a general approach to define a many-valued preferential interpretation of gradual argumentation semantics. The approach allows for conditional reasoning over arguments and boolean combination of arguments, with…

Artificial Intelligence · Computer Science 2025-06-10 Mario Alviano , Laura Giordano , Daniele Theseider Dupré

Despite a growing literature on explaining neural networks, no consensus has been reached on how to explain a neural network decision or how to evaluate an explanation. Our contributions in this paper are twofold. First, we investigate…

Machine Learning · Computer Science 2020-03-23 Laura Rieger , Lars Kai Hansen

This paper presents Abduction and Argumentation as two principled forms for reasoning, and fleshes out the fundamental role that they can play within Machine Learning. It reviews the state-of-the-art work over the past few decades on the…

Artificial Intelligence · Computer Science 2020-10-27 Antonis Kakas , Loizos Michael

Dung's famous abstract argumentation frameworks represent the core formalism for many problems and applications in the field of argumentation which significantly evolved within the last decade. Recent work in the field has thus focused on…

Artificial Intelligence · Computer Science 2016-04-20 Wolfgang Dvořák , Sarah Alice Gaggl , Johannes Wallner , Stefan Woltran

Repeated executions of reasoning tasks for varying inputs are necessary in many applicative settings, such as stream reasoning. In this context, we propose an incremental grounding approach for the answer set semantics. We focus on the…

Artificial Intelligence · Computer Science 2020-02-19 Francesco Calimeri , Giovambattista Ianni , Francesco Pacenza , Simona Perri , Jessica Zangari

We introduce a non-wellfounded proof system for intuitionistic logic extended with inductive and co-inductive definitions, based on a syntax in which fixpoint formulas are annotated with explicit variables for ordinals. We explore the…

Logic in Computer Science · Computer Science 2026-05-13 Sebastian Enqvist

In previous papers on this project a general static logical framework for formalizing and mechanizing set theories of different strength was suggested, and the power of some predicatively acceptable theories in that framework was explored.…

Logic in Computer Science · Computer Science 2023-06-22 Arnon Avron , Liron Cohen