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

arXiv: https://arxiv.org/abs/2401.08879 · HTML: https://mlsanity.com/paper/2401.08879/

## 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 (most cited first, 9 of 9)

- [A Unified Approach to Interpreting Model Predictions](https://mlsanity.com/paper/1705.07874/) (2017)
- ["Why Should I Trust You?": Explaining the Predictions of Any Classifier](https://mlsanity.com/paper/1602.04938/) (2016)
- [Model Agnostic Supervised Local Explanations](https://mlsanity.com/paper/1807.02910/) (2018)
- [Argumentative XAI: A Survey](https://mlsanity.com/paper/2105.11266/) (2021)
- [Interpreting Neural Networks as Gradual Argumentation Frameworks (Including Proof Appendix)](https://mlsanity.com/paper/2012.05738/) (2020)
- [SpArX: Sparse Argumentative Explanations for Neural Networks [Technical Report]](https://mlsanity.com/paper/2301.09559/) (2023)
- [Explaining Random Forests using Bipolar Argumentation and Markov Networks (Technical Report)](https://mlsanity.com/paper/2211.11699/) (2022)
- [Argument Attribution Explanations in Quantitative Bipolar Argumentation Frameworks (Technical Report)](https://mlsanity.com/paper/2307.13582/) (2023)
- [A Tutorial for Weighted Bipolar Argumentation with Continuous Dynamical Systems and the Java Library Attractor](https://mlsanity.com/paper/1811.12787/) (2018)

## Built on by (most cited first, 11 of 11)

- [Argumentative Large Language Models for Explainable and Contestable Claim Verification](https://mlsanity.com/paper/2405.02079/) (2024)
- [Impact Measures for Gradual Argumentation Semantics](https://mlsanity.com/paper/2407.08302/) (2024)
- [CE-QArg: Counterfactual Explanations for Quantitative Bipolar Argumentation Frameworks (Technical Report)](https://mlsanity.com/paper/2407.08497/) (2024)
- [A Methodology for Incompleteness-Tolerant and Modular Gradual Semantics for Argumentative Statement Graphs](https://mlsanity.com/paper/2410.22209/) (2024)
- [Contestability in Quantitative Argumentation](https://mlsanity.com/paper/2507.11323/) (2025)
- [Set Contribution Functions for Quantitative Bipolar Argumentation and their Principles](https://mlsanity.com/paper/2509.14963/) (2025)
- [Abstract Weighted Based Gradual Semantics in Argumentation Theory](https://mlsanity.com/paper/2401.11472/) (2024)
- [Applying Attribution Explanations in Truth-Discovery Quantitative Bipolar Argumentation Frameworks](https://mlsanity.com/paper/2409.05831/) (2024)
- [Multi-User Personalisation in Human-Robot Interaction: Resolving Preference Conflicts Using Gradual Argumentation](https://mlsanity.com/paper/2511.03576/) (2025)
- [Argumentation for Common Ground: Finding Zones of Possible Agreement between Individuals in Conflict](https://mlsanity.com/paper/2608.15634/) (2026)
- [Contrastive Explanations in Quantitative Bipolar Argumentation Frameworks](https://mlsanity.com/paper/2609.02399/) (2026)

## 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.