Explainable and Robust Automatic Fact Checking

Project Information

ExplainYourself

Grant agreement ID: 101077481

DOI

10.3030/101077481

EC signature date 17 December 2022

Start date 1 September 2023

End date 31 August 2028

Funded under

• European Research Council (ERC)

Total cost

€ 1 498 616,00

EU contribution

€ 1 498 616,00

Coordinated by

KOBENHAVNS UNIVERSITET
Denmark

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Conference proceedings (15)

Explaining Interactions Between Text Spans

Author(s): Sagnik Choudhury, Pepa Atanasova, Isabelle Augenstein
Published in: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Publisher: Association for Computational Linguistics
DOI: 10.18653/V1/2023.EMNLP-MAIN.783

Can Community Notes Replace Professional Fact-Checkers?

Author(s): Nadav Borenstein, Greta Warren, Desmond Elliott, Isabelle Augenstein
Published in: Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2025
Publisher: Association for Computational Linguistics
DOI: 10.18653/V1/2025.ACL-SHORT.42

Evaluating Input Feature Explanations through a Unified Diagnostic Evaluation Framework

Author(s): Jingyi Sun, Pepa Atanasova, Isabelle Augenstein
Published in: Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2025
Publisher: Association for Computational Linguistics
DOI: 10.18653/V1/2025.NAACL-LONG.530

Faithfulness Tests for Natural Language Explanations

Author(s): Pepa Atanasova, Oana-Maria Camburu, Christina Lioma, Thomas Lukasiewicz, Jakob Grue Simonsen, Isabelle Augenstein
Published in: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023
Publisher: Association for Computational Linguistics
DOI: 10.18653/V1/2023.ACL-SHORT.25

Revealing the Parametric Knowledge of Language Models: A Unified Framework for Attribution Methods

Author(s): Yu, Haeun; Atanasova, Pepa; Augenstein, Isabelle
Published in: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
Publisher: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2404.18655

Efficiency and Effectiveness of LLM-Based Summarization of Evidence in Crowdsourced Fact-Checking

Author(s): Kevin Roitero, Dustin Wright, Michael Soprano, Isabelle Augenstein, Stefano Mizzaro
Published in: Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025
Publisher: ACM
DOI: 10.1145/3726302.3729960

Factcheck-Bench: Fine-Grained Evaluation Benchmark for Automatic Fact-checkers

Author(s): Yuxia Wang, Revanth Gangi Reddy, Zain Muhammad Mujahid, Arnav Arora, Aleksandr Rubashevskii, Jiahui Geng, Osama Mohammed Afzal, Liangming Pan, Nadav Borenstein, Aditya Pillai, Isabelle Augenstein, Iryna Gurevych, Preslav Nakov
Published in: Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
Publisher: Association for Computational Linguistics
DOI: 10.18653/V1/2024.FINDINGS-EMNLP.830

A Reality Check on Context Utilisation for Retrieval-Augmented Generation

Author(s): Lovisa Hagström, Sara Vera Marjanovic, Haeun Yu, Arnav Arora, Christina Lioma, Maria Maistro, Pepa Atanasova, Isabelle Augenstein
Published in: Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
Publisher: Association for Computational Linguistics
DOI: 10.18653/V1/2025.ACL-LONG.968

Show Me the Work: Fact-Checkers' Requirements for Explainable Automated Fact-Checking

Author(s): Greta Warren; Irina Shklovski; Isabelle Augenstein
Published in: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, 2025
DOI: 10.48550/ARXIV.2502.09083

SynDARin: Synthesising Datasets for Automated Reasoning in Low-Resource Languages

Author(s): Gayane Ghazaryan, Erik Arakelyan, Isabelle Augenstein, Pasquale Minervini
Published in: Proceedings of the 31st International Conference on Computational Linguistics, 2025
Publisher: Association for Computational Linguistics

Investigating the Impact of Model Instability on Explanations and Uncertainty

Author(s): Sara Marjanovic, Isabelle Augenstein, Christina Lioma
Published in: Findings of the Association for Computational Linguistics ACL 2024, 2024
Publisher: Association for Computational Linguistics
DOI: 10.18653/V1/2024.FINDINGS-ACL.705

Measuring and Benchmarking Large Language Models’ Capabilities to Generate Persuasive Language

Author(s): Amalie Brogaard Pauli, Isabelle Augenstein, Ira Assent
Published in: Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2025
Publisher: Association for Computational Linguistics
DOI: 10.18653/V1/2025.NAACL-LONG.506

LLM Tropes: Revealing Fine-Grained Values and Opinions in Large Language Models

Author(s): Dustin Wright, Arnav Arora, Nadav Borenstein, Srishti Yadav, Serge Belongie, Isabelle Augenstein
Published in: Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
Publisher: Association for Computational Linguistics
DOI: 10.18653/V1/2024.FINDINGS-EMNLP.995

People Make Better Edits: Measuring the Efficacy of LLM-Generated Counterfactually Augmented Data for Harmful Language Detection

Author(s): Indira Sen, Dennis Assenmacher, Mattia Samory, Isabelle Augenstein, Wil Aalst, Claudia Wagner
Published in: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Publisher: Association for Computational Linguistics
DOI: 10.18653/V1/2023.EMNLP-MAIN.649

DYNAMICQA:Tracing Internal Knowledge Conflicts in Language Models

Author(s): Marjanović, Sara Vera; Yu, Haeun; Atanasova, Pepa; Maistro, Maria; Lioma, Christina; Augenstein, Isabelle
Published in: Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
DOI: 10.18653/V1/2024.FINDINGS-EMNLP.838

Peer reviewed articles (1)

Factuality challenges in the era of large language models and opportunities for fact-checking

Author(s): Isabelle Augenstein; Timothy Baldwin; Meeyoung Cha; Tanmoy Chakraborty; Giovanni Luca Ciampaglia; David Corney; Renee DiResta; Emilio Ferrara; Scott Hale; Alon Halevy; Eduard Hovy; Heng Ji; Filippo Menczer; Ruben Miguez; Preslav Nakov; Dietram Scheufele; Shivam Sharma; Giovanni Zagni
Published in: Nature Machine Intelligence, 2024, ISSN 2522-5839
Publisher: Nature
DOI: 10.1038/S42256-024-00881-Z