{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:21:44Z","timestamp":1785543704668,"version":"3.56.0"},"reference-count":82,"publisher":"MIT Press","license":[{"start":{"date-parts":[[2024,4,12]],"date-time":"2024-04-12T00:00:00Z","timestamp":1712880000000},"content-version":"vor","delay-in-days":102,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["direct.mit.edu"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,4,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Justification is an explanation that supports the veracity assigned to a claim in fact-checking. However, the task of justification generation has been previously oversimplified as summarization of a fact-check article authored by fact-checkers. Therefore, we propose a realistic approach to generate justification based on retrieved evidence. We present a new benchmark dataset called ExClaim (for Explainable fact-checking of real-world Claims), and introduce JustiLM, a novel few-shot Justification generation based on retrieval-augmented Language Model by using fact-check articles as an auxiliary resource during training only. Experiments show that JustiLM achieves promising performance in justification generation compared to strong baselines, and can also enhance veracity classification with a straightforward extension.1<\/jats:p>\n               <jats:p>Code and dataset are released at https:\/\/github.com\/znhy1024\/JustiLM.<\/jats:p>","DOI":"10.1162\/tacl_a_00649","type":"journal-article","created":{"date-parts":[[2024,4,12]],"date-time":"2024-04-12T19:02:51Z","timestamp":1712948571000},"page":"334-354","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":16,"title":["JustiLM: Few-shot Justification Generation for Explainable Fact-Checking of Real-world Claims"],"prefix":"10.1162","volume":"12","author":[{"given":"Fengzhu","family":"Zeng","sequence":"first","affiliation":[{"name":"Singapore Management University 80 Stamford Rd, Singapore 178902. 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