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Our findings underscore the dominance of BERT-based methods in achieving state-of-the-art results for RE while also noting the promising capabilities of emerging Large Language Models (LLMs) like T5, especially in few-shot relation extraction scenarios where they excel in identifying previously unseen relations.<\/jats:p>","DOI":"10.1007\/s10462-025-11280-0","type":"journal-article","created":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T07:35:30Z","timestamp":1751355330000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["A survey on cutting-edge relation extraction techniques based on language models"],"prefix":"10.1007","volume":"58","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9263-1402","authenticated-orcid":false,"given":"Jose A.","family":"Diaz-Garcia","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julio Amador Diaz","family":"Lopez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,1]]},"reference":[{"key":"11280_CR1","unstructured":"Agosti M, Di Nunzio G, Marchesin S, Silvello G et al (2018) A relation extraction approach for clinical decision support. 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