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The task consists of the subtasks of retrieving the relevant documents (and sentences) from Wikipedia and validating whether the information in the documents supports or refutes a given claim. This task is essential and can be the building block of applications such as fake news detection and medical claim verification. In this article, we aim at a better understanding of the challenges of the task by presenting the literature in a structured and comprehensive way. We describe the proposed methods by analyzing the technical perspectives of the different approaches and discussing the performance results on the FEVER dataset, which is the most well-studied and formally structured dataset on the fact extraction and verification task. We also conduct the largest experimental study to date on identifying beneficial loss functions for the sentence retrieval component. Our analysis indicates that sampling negative sentences is important for improving the performance and decreasing the computational complexity. Finally, we describe open issues and future challenges, and we motivate future research in the task.<\/jats:p>","DOI":"10.1145\/3485127","type":"journal-article","created":{"date-parts":[[2021,11,23]],"date-time":"2021-11-23T17:36:59Z","timestamp":1637689019000},"page":"1-35","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":27,"title":["A Review on Fact Extraction and Verification"],"prefix":"10.1145","volume":"55","author":[{"given":"Giannis","family":"Bekoulis","sequence":"first","affiliation":[{"name":"ETRO Department, Vrije Universiteit Brussel, Belgium and imec, Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christina","family":"Papagiannopoulou","sequence":"additional","affiliation":[{"name":"ETRO Department, Vrije Universiteit Brussel, Belgium and imec, Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikos","family":"Deligiannis","sequence":"additional","affiliation":[{"name":"ETRO Department, Vrije Universiteit Brussel, Belgium and imec, Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2021,11,23]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3084806"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.36370\/tto.2019.15"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W18-5513"},{"key":"e_1_3_2_5_2","volume-title":"Proceedings of CLEF (Working Notes)","author":"Atanasova Pepa","year":"2019","unstructured":"Pepa Atanasova, Preslav Nakov, Georgi Karadzhov, Mitra Mohtarami, and Giovanni Da San Martino. 2019. 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