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Traditional rule\u2013based and machine learning (ML) detection methods have demonstrated limitations in adaptability and generalization. This paper proposes SpamLLM, a multimodal spam detection framework that leverages a frozen large language model (LLM) backbone integrated with semantic embeddings and structured metadata extracted from email headers and body statistics. Rigorous evaluations are conducted across four widely used spam detection datasets, and SpamLLM is compared against classical ML, deep learning, and pretrained Transformer\u2010based baseline models. The experimental results demonstrate that SpamLLM outperforms existing methods and achieves state\u2010of\u2010the\u2010art performance in accuracy, precision, recall, and F1 score. Notably, SpamLLM excels in handling diverse spam content and provides robust detection across various datasets. These findings underscore the potential of multimodal fusion approaches for advancing spam classification systems and suggest promising directions for future research in email security.<\/jats:p>","DOI":"10.1155\/int\/2309553","type":"journal-article","created":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T10:47:44Z","timestamp":1782211664000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SpamLLM: Leveraging Large Language Models for Robust Spam Email Classification"],"prefix":"10.1155","volume":"2026","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2379-9807","authenticated-orcid":false,"given":"Zhiyong","family":"He","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2420-8278","authenticated-orcid":false,"given":"Chang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9803-6672","authenticated-orcid":false,"given":"Boyang","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8807-1385","authenticated-orcid":false,"given":"Duo","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,6,23]]},"reference":[{"key":"e_1_2_13_1_2","doi-asserted-by":"crossref","unstructured":"Gomez HidalgoJ. 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