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A Survey of Large Language Models for European Languages

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arxiv 2408.15040 v2 pith:TBY3CWQQ submitted 2024-08-27 cs.CL

A Survey of Large Language Models for European Languages

classification cs.CL
keywords languagelargellmsmodelseuropeanlanguagesadvancingattention
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Large Language Models (LLMs) have gained significant attention due to their high performance on a wide range of natural language tasks since the release of ChatGPT. The LLMs learn to understand and generate language by training billions of model parameters on vast volumes of text data. Despite being a relatively new field, LLM research is rapidly advancing in various directions. In this paper, we present an overview of LLM families, including LLaMA, PaLM, GPT, and MoE, and the methods developed to create and enhance LLMs for official European Union (EU) languages. We provide a comprehensive summary of common monolingual and multilingual datasets used for pretraining large language models.

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