@inproceedings{milner-etal-2026-browser,
title = "A Browser-based Open Source Assistant for Multimodal Content Verification",
author = "Milner, Rosanna and
Foster, Michael and
Razuvayevskaya, Olesya and
Porcellini, Valentin and
Teyssou, Denis and
Roberts, Ian and
Bontcheva, Kalina",
editor = "Croce, Danilo and
Leidner, Jochen and
Moosavi, Nafise Sadat",
booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 3: System Demonstrations)",
month = mar,
year = "2026",
address = "Rabat, Marocco",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.eacl-demo.12/",
pages = "154--162",
ISBN = "979-8-89176-382-1",
abstract = "Disinformation and advanced generative AI content pose a significant challenge for journalists and fact-checkers who must rapidly verify digital media. While many NLP models exist for detecting signals like persuasion techniques, subjectivity, and AI-generated text, they 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, presenting actionable credibility signals, AI-generation likelihood, and other verification advice in an easy-to-digest format. This paper will showcase the tool{'}s architecture, its integration of multiple NLP services, and its real-world application for detecting disinformation."
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%0 Conference Proceedings
%T A Browser-based Open Source Assistant for Multimodal Content Verification
%A Milner, Rosanna
%A Foster, Michael
%A Razuvayevskaya, Olesya
%A Porcellini, Valentin
%A Teyssou, Denis
%A Roberts, Ian
%A Bontcheva, Kalina
%Y Croce, Danilo
%Y Leidner, Jochen
%Y Moosavi, Nafise Sadat
%S Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations)
%D 2026
%8 March
%I Association for Computational Linguistics
%C Rabat, Marocco
%@ 979-8-89176-382-1
%F milner-etal-2026-browser
%X Disinformation and advanced generative AI content pose a significant challenge for journalists and fact-checkers who must rapidly verify digital media. While many NLP models exist for detecting signals like persuasion techniques, subjectivity, and AI-generated text, they 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, presenting actionable credibility signals, AI-generation likelihood, and other verification advice in an easy-to-digest format. This paper will showcase the tool’s architecture, its integration of multiple NLP services, and its real-world application for detecting disinformation.
%U https://aclanthology.org/2026.eacl-demo.12/
%P 154-162
Markdown (Informal)
[A Browser-based Open Source Assistant for Multimodal Content Verification](https://aclanthology.org/2026.eacl-demo.12/) (Milner et al., EACL 2026)
ACL
- Rosanna Milner, Michael Foster, Olesya Razuvayevskaya, Valentin Porcellini, Denis Teyssou, Ian Roberts, and Kalina Bontcheva. 2026. A Browser-based Open Source Assistant for Multimodal Content Verification. In Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 154–162, Rabat, Marocco. Association for Computational Linguistics.