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Addressing this gap, our study leverages a metalinguistic approach that uses advanced meta-learning techniques to enhance the detection capabilities across bilingual texts, effectively linking technical advancements directly to the pressing social issue of hate speech. In this study, we introduce techniques that adapt models that deal with hate speech detection within the same languages (intra-lingual), across different languages (cross-lingual), and techniques that adapt models to new languages with minimal extra training, independent of the model type (cross-lingual model-agnostic meta-learning-based approaches) for bilingual text analysis in Norwegian and English. Our methodology incorporates attention mechanisms (components that help the model focus on relevant parts of the text) and adaptive learning rate schedulers (tools that adjust the learning speed based on performance). Our methodology incorporates components that help the model focus on relevant parts of the text (attention mechanisms) and tools that adjust the learning speed based on performance (adaptive learning rate schedulers). We conducted various experiments using language-specific and multilingual transformers. Among these, the combination of Nor-BERT and LSTM with zero-shot and few-shot model-agnostic meta-learning achieved remarkable F1 scores of 79% and 90%, highlighting the effectiveness of our proposed framework.<\/jats:p>","DOI":"10.1007\/s40747-025-01808-w","type":"journal-article","created":{"date-parts":[[2025,2,27]],"date-time":"2025-02-27T06:24:09Z","timestamp":1740637449000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Metalinguist: enhancing hate speech detection with cross-lingual meta-learning"],"prefix":"10.1007","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2526-9899","authenticated-orcid":false,"given":"Ehtesham","family":"Hashmi","sequence":"first","affiliation":[]},{"given":"Sule Yildirim","family":"Yayilgan","sequence":"additional","affiliation":[]},{"given":"Mohamed","family":"Abomhara","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,2,27]]},"reference":[{"key":"1808_CR1","unstructured":"AI@Meta (2024) Llama 3 model card https:\/\/github.com\/meta-llama\/llama3\/blob\/main\/MODEL_CARD.md. 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