A Browser-based Open Source Assistant for Multimodal Content Verification

• URL: http://arxiv.org/abs/2603.02842v1
• Date: Tue, 03 Mar 2026 10:39:32 GMT
• Title: A Browser-based Open Source Assistant for Multimodal Content Verification
• Authors: Rosanna Milner, Michael Foster, Olesya Razuvayevskaya, Ian Roberts, Valentin Porcellini, Denis Teyssou, Kalina Bontcheva,
• Abstract summary: Disinformation and false content produced by generative AI pose a significant challenge for journalists and fact-checkers.<n>There is an abundance of NLP models for detecting credibility signals such as persuasion techniques, subjectivity, or machine-generated text.<n>This paper demonstrates the VERIFICATION ASSISTANT, a browser-based tool designed to bridge this gap.
• Score: 5.0488681454219675
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Disinformation and false content produced by generative AI pose a significant challenge for journalists and fact-checkers who must rapidly verify digital media information. While there is an abundance of NLP models for detecting credibility signals such as persuasion techniques, subjectivity, or machine-generated text, such methods often remain inaccessible to non-expert users and are not integrated into their daily workflows as a unified framework. This paper demonstrates the VERIFICATION ASSISTANT, a browser-based tool designed to bridge this gap. The VERIFICATION ASSISTANT, a core component of the widely adopted VERIFICATION PLUGIN (140,000+ users), allows users to submit URLs or media files to a unified interface. It automatically extracts content and routes it to a suite of backend NLP classifiers, delivering actionable credibility signals, estimating AI-generated content, and providing other verification guidance in a clear, easy-to-digest format. This paper showcases the tool architecture, its integration of multiple NLP services, and its real-world application to detecting disinformation.

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