mlsanityData to 7 Oct 2026

Strength Change Explanations in Quantitative Argumentation

arXiv 2603.00008 ↗First posted 26 Jan 2026cs.MA cs.AI cs.LOcited by 2

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Abstract (arXiv)

In order to make argumentation-based inference contestable, it is crucial to explain what changes can achieve a desired (instead of the contested) inference result. To this end, we introduce strength change explanations for quantitative (bipolar) argumentation graphs. Strength change explanations describe changes to the initial strengths of a subset of the arguments in a given graph that can achieve a desired ordering based on the final strengths of some (potentially different) subset of arguments. We show that the existing notions of inverse and counterfactual problems can be reduced to strength change explanations. We also prove basic soundness and completeness properties of our strength change explanations, and demonstrate their existence and non-existence in some special cases. By applying a heuristic search, we demonstrate that we can often successfully find strength change explanations for layered graphs that are common in typical application scenarios; still, limitations remain for settings where we do not provide guarantees for the presence (or absence) of explanations.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 6 of its 29 references that are in the map. First posted on arXiv 26 Jan 2026.

Builds on

6 of 29 references.

References · 6

  1. 2021Argumentative XAI: A Surveycited by 66
  2. 2020Interpreting Neural Networks as Gradual Argumentation Frameworks (Including Proof Appendix)cited by 38
  3. 2018Modular Semantics and Characteristics for Bipolar Weighted Argumentation Graphscited by 23
  4. 2024Impact Measures for Gradual Argumentation Semanticscited by 5
  5. 2025Change in Quantitative Bipolar Argumentation: Sufficient, Necessary, and Counterfactual Explanationscited by 4
  6. 2024Visualizing Extensions of Argumentation Frameworks as Layered Graphscited by 1

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Citing papers per year: 2026: 2.

2 papers.