mlsanityData to 14 Oct 2026

Contribution Functions for Quantitative Bipolar Argumentation Graphs: A Principle-based Analysis

arXiv 2401.08879 ↗First posted 16 Jan 2024cs.AIcited by 11

Not on the map. Why?

Abstract (arXiv)

We present a principle-based analysis of contribution functions for quantitative bipolar argumentation graphs that quantify the contribution of one argument to another. The introduced principles formalise the intuitions underlying different contribution functions as well as expectations one would have regarding the behaviour of contribution functions in general. As none of the covered contribution functions satisfies all principles, our analysis can serve as a tool that enables the selection of the most suitable function based on the requirements of a given use case.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 9 of its 34 references that are in the map. First posted on arXiv 16 Jan 2024.

Builds on

9 of 34 references.

References · 9

  1. 2017A Unified Approach to Interpreting Model Predictionscited by 6,555
  2. 2016"Why Should I Trust You?": Explaining the Predictions of Any Classifiercited by 5,070
  3. 2018Model Agnostic Supervised Local Explanationscited by 83
  4. 2021Argumentative XAI: A Surveycited by 67
  5. 2020Interpreting Neural Networks as Gradual Argumentation Frameworks (Including Proof Appendix)cited by 39
  6. 2023SpArX: Sparse Argumentative Explanations for Neural Networks [Technical Report]cited by 18
  7. 2022Explaining Random Forests using Bipolar Argumentation and Markov Networks (Technical Report)cited by 9
  8. 2023Argument Attribution Explanations in Quantitative Bipolar Argumentation Frameworks (Technical Report)cited by 7
  9. 2018A Tutorial for Weighted Bipolar Argumentation with Continuous Dynamical Systems and the Java Library Attractorcited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 6; 2025: 3; 2026: 2.

11 papers.

  1. 2024Argumentative Large Language Models for Explainable and Contestable Claim Verificationcited by 36
  2. 2024Impact Measures for Gradual Argumentation Semanticscited by 5
  3. 2024CE-QArg: Counterfactual Explanations for Quantitative Bipolar Argumentation Frameworks (Technical Report)cited by 3
  4. 2024A Methodology for Incompleteness-Tolerant and Modular Gradual Semantics for Argumentative Statement Graphscited by 3
  5. 2025Contestability in Quantitative Argumentationcited by 3
  6. 2025Set Contribution Functions for Quantitative Bipolar Argumentation and their Principlescited by 2
  7. 2024Abstract Weighted Based Gradual Semantics in Argumentation Theorycited by 1
  8. 2024Applying Attribution Explanations in Truth-Discovery Quantitative Bipolar Argumentation Frameworkscited by 1
  9. 2025Multi-User Personalisation in Human-Robot Interaction: Resolving Preference Conflicts Using Gradual Argumentationcited by 0
  10. 2026Argumentation for Common Ground: Finding Zones of Possible Agreement between Individuals in Conflictcited by 0
  11. 2026Contrastive Explanations in Quantitative Bipolar Argumentation Frameworkscited by 0