{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T21:41:30Z","timestamp":1780609290641,"version":"3.54.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:p>Journalistic manual fact-checking is the usual way to address fake news; however, this labor-intensive task regularly is not a match for the scale of the problem. The literature introduced automated fact-checking (AFC) as a potential solution; however, there is still missing functionality in the AFC pipeline, a lack of research benchmarking data, and a disconnect between their design and human factors crucial for adoption. We present a fully explainable AFC framework designed to augment professional journalists in the wild. A novel human annotation-free approach surpasses state-of-the-art multi-label classification by 12%. It is the first to demonstrate strong generalization across different claim subjects without retraining and to generate complete verdict explanation articles and their summaries. A focused user study of 103 professional journalists, with 93% having dedicated experience with fact-checking, validates the framework's level of explainability, transparency, and quality of generated fact-checking artifacts. The importance of establishing clear source selection and bias evaluation criteria reinforced the need for human augmentation, not replacement, by AFC systems.<\/jats:p>","DOI":"10.24963\/ijcai.2025\/1140","type":"proceedings-article","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T08:10:40Z","timestamp":1758269440000},"page":"10262-10270","source":"Crossref","is-referenced-by-count":2,"title":["Explainable Automatic Fact-Checking for Journalists Augmentation in the Wild"],"prefix":"10.24963","author":[{"given":"Filipe","family":"Altoe","sequence":"first","affiliation":[{"name":"INESC-ID\/Instituto Superior Tecnico - Universidade de Lisboa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S\u00e9rgio Miguel Gon\u00e7alves","family":"Pinto","sequence":"additional","affiliation":[{"name":"INESC-ID\/Instituto Superior Tecnico - Universidade de Lisboa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"H Sofia","family":"Pinto","sequence":"additional","affiliation":[{"name":"INESC-ID\/Instituto Superior Tecnico - Universidade de Lisboa"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Thirty-Fourth International Joint Conference on Artificial Intelligence {IJCAI-25}","theme":"Artificial Intelligence","location":"Montreal, Canada","acronym":"IJCAI-2025","number":"34","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2025,8,16]]},"end":{"date-parts":[[2025,8,22]]}},"container-title":["Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T11:36:15Z","timestamp":1758627375000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2025\/1140"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2025\/1140","relation":{},"subject":[],"published":{"date-parts":[[2025,9]]}}}