Contestable Multi-Agent Debate with Arena-based Argumentative Computation for Multimedia Verification

TL;DR

This paper introduces a multi-agent framework for multimedia verification that emphasizes transparent, contestable reasoning using argumentation graphs, multimodal models, and external tools, with practical, editable reports.

Contribution

It presents a novel arena-based argumentation approach integrating multimodal models and external verification tools for transparent multimedia reasoning.

Findings

System generates transparent, section-wise verification reports.

Arguments are supported with provenance and strength scores.

Implementation is publicly available at the provided GitHub URL.

Abstract

Multimedia verification requires not only accurate conclusions but also transparent and contestable reasoning. We propose a contestable multi-agent framework that integrates multimodal large language models, external verification tools, and arena-based quantitative bipolar argumentation (A-QBAF) as a submission to the ICMR 2026 Grand Challenge on Multimedia Verification. Our method decomposes each case into claim-centered sections, retrieves targeted evidence, and converts evidence into structured support and attack arguments with provenance and strength scores. These arguments are resolved through small local argument graphs with selective clash resolution and uncertainty-aware escalation. The resulting system generates section-wise verification reports that are transparent, editable, and computationally practical for real-world multimedia verification. Our implementation is public at: https://github.com/Analytics-Everywhere-Lab/MV2026_the_liems.