Veracity: An Open-Source AI Fact-Checking System

Curtis, Taylor Lynn; Puelma Touzel, Maximilian; Garneau, William; Gruaz, Manon; Pinder, Mike; Wang, Li Wei; Krishna, Sukanya; Cohen, Luda; Godbout, Jean-François; Rabbany, Reihaneh; Pelrine, Kellin

doi:10.24963/ijcai.2025/1254

Veracity: An Open-Source AI Fact-Checking System

Taylor Lynn Curtis, Maximilian Puelma Touzel, William Garneau, Manon Gruaz, Mike Pinder, Li Wei Wang, Sukanya Krishna, Luda Cohen, Jean-François Godbout, Reihaneh Rabbany, Kellin Pelrine

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Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. Demo Track. Pages 11021-11024.

https://doi.org/10.24963/ijcai.2025/1254

Keywords

Multidisciplinary Topics and Applications: MTA: News and media
Humans and AI: HAI: Human-computer interaction
Multidisciplinary Topics and Applications: MTA: Software engineering
AI Ethics, Trust, Fairness: ETF: Trustworthy AI

Abstract

The proliferation of misinformation poses a significant threat to society, exacerbated by the capabilities of generative AI.

This demo paper introduces Veracity, an open-source AI system designed to empower individuals to combat misinformation through transparent and accessible fact-checking. Veracity leverages the synergy between Large Language Models (LLMs) and web retrieval agents to analyze user-submitted claims and provide grounded veracity assessments with intuitive explanations. Key features include multilingual support, numerical scoring of claim veracity, and an interactive interface inspired by familiar messaging applications. This paper will showcase Veracity's ability to not only detect misinformation but also explain its reasoning, fostering media literacy and promoting a more informed society.

Taylor Lynn Curtis, Maximilian Puelma Touzel, William Garneau, Manon Gruaz, Mike Pinder, Li Wei Wang, Sukanya Krishna, Luda Cohen, Jean-François Godbout, Reihaneh Rabbany, and Kellin Pelrine. 2025. Veracity: An Open-Source AI Fact-Checking System. In Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25. IJCAI, 11021–11024. https://doi.org/10.24963/ijcai.2025/1254

@inproceedings{ijcai2025p1254,
  title     = {Veracity: An Open-Source AI Fact-Checking System},
  author    = {Curtis, Taylor Lynn and Puelma Touzel, Maximilian and Garneau, William and Gruaz, Manon and Pinder, Mike and Wang, Li Wei and Krishna, Sukanya and Cohen, Luda and Godbout, Jean-François and Rabbany, Reihaneh and Pelrine, Kellin},
  booktitle = {Proceedings of the Thirty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-25}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {James Kwok},
  pages     = {11021--11024},
  year      = {2025},
  month     = {8},
  note      = {Demo Track},
  doi       = {10.24963/ijcai.2025/1254},
  url       = {https://doi.org/10.24963/ijcai.2025/1254},
}

TY  - CPAPER
TI  - Veracity: An Open-Source AI Fact-Checking System
AU  - Curtis, Taylor Lynn
AU  - Puelma Touzel, Maximilian
AU  - Garneau, William
AU  - Gruaz, Manon
AU  - Pinder, Mike
AU  - Wang, Li Wei
AU  - Krishna, Sukanya
AU  - Cohen, Luda
AU  - Godbout, Jean-François
AU  - Rabbany, Reihaneh
AU  - Pelrine, Kellin
T2  - Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2025
SP  - 11021
EP  - 11024
DO  - 10.24963/ijcai.2025/1254
UR  - https://doi.org/10.24963/ijcai.2025/1254
ER  -