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.
Quantitative Measurement of Language Distance among Closely Related Indo-European Languages Using Pretrained Language Models: A Case Study on the North Germanic Branch
CLARIN-PT-LDB: An Open LLM Leaderboard for Portuguese to assess Language, Culture and Civility
University of Lisbon NLX—Grupo de Fala e Linguagem Natural, Departmento de Informática Faculdade de Ciências, Campo Grande, 1749-016 Lisboa, Portugal（里斯本大学 NLX—语言与语言自然组，计算机学院，Campo Grande, 1749-016里斯本，葡萄牙）
Charting the European LLM Benchmarking Landscape: A New Taxonomy and a Set of Best Practices
Jožef Stefan Institute（乔塞夫·斯塔芬研究所）；University of Ljubljana（卢布尔雅那大学）；Faculty of Arts, University of Ljubljana（艺术学院，卢布尔雅那大学）；Faculty of Computer and Information Science, University of Ljubljana（计算机与信息科学学院，卢布尔雅那大学）；Institute of Contemporary History（现代史研究所）
AMALIA Technical Report: A Fully Open Source Large Language Model for European Portuguese
NOVA School of Science and Technology（新大学科学与技术学院）；NOVA LINCS（新大学LINCS实验室）；Instituto de Telecomunicações（电信研究所）；Instituto Superior Técnico, Universidade de Lisboa（里斯本大学高等技术学院）；Fundação para a Ciência e Tecnologia（科学技术基金会）
Unbabel；Instituto de Telecomunicações & Instituto Superior Técnico, Universidade de Lisboa（电信研究院 & 莱斯特大学技术学院）；Carnegie Mellon University（卡内基梅隆大学）；MICS, CentraleSupélec, Université Paris-Saclay（MICS、中央圣埃克苏佩里学院、巴黎萨克雷大学）；Illuin Technology（Illuin技术公司）；University of Edinburgh（爱丁堡大学）；Equall（Equall公司）；Aveni（Aveni公司）；Sorbonne Université, CNRS, ISIR（索邦大学、国家科学研究中心、ISIR）；Diabolocom（Diabolocom公司）
Superhuman performance in urology board questions by an explainable large language model enabled for context integration of the European Association of Urology guidelines: the UroBot study
German Cancer Research Center (DKFZ)（德国癌症研究中心）；University Medical Center Mannheim, Ruprecht-Karls University of Heidelberg（海德堡大学曼海姆医学院）；University of Heidelberg（海德堡大学）
Fine PT-PT Web: A High-Quality 41 Billion Tokens Data Collection of the European Portuguese Web
NOVA School of Science and Technology（NOVA科学与技术学院）；NOVA LINCS；Fundação para a Ciência e Tecnologia（科学技术基金会）；Instituto Superior Técnico, Universidade de Lisboa（里斯本大学高等技术学院）；Instituto de Telecomunicações（电信研究院）
Development of a European Union Time-Indexed Reference Dataset for Assessing the Performance of Signal Detection Methods in Pharmacovigilance using a Large Language Model
Department of Drug Design and Pharmacology, University of Copenhagen（哥本哈根大学药物设计与药理学系）；GSK（葛兰素史克）
Instituto Superior Técnico & Universidade de Lisboa (Lisbon ELLIS Unit)（里斯本ELLIS单位（理工学院与里斯本大学））；Instituto de Telecomunicações（电信研究院）；MICS, CentraleSupélec, Université Paris-Saclay（MICS、中央圣艾尔布兰理工大学、巴黎萨克雷大学）；Acolad；Carnegie Mellon University（卡内基梅隆大学）；University of Edinburgh（爱丁堡大学）；Diabolocom；Aveni；OutSystems；Sword Health；Sorbonne Université, CNRS, ISIR（索邦大学、国家科学研究中心、ISIR）；Artefact Research Center（Artefact研究机构）；TransPerfect
DFKI GmbH（德国人工智能研究中心）；ILSP/Athena RC（雅典研究中心语言处理研究所）；University of Sheffield（谢菲尔德大学）；Charles University（查理大学）；Evaluations and Language Resources Distribution Agency (ELDA)（语言资源评估与分发机构）；Tilde（蒂尔代公司）；SAIL LABS Technology GmbH（SAIL LABS技术公司）；Expert System Iberia SL（伊比利亚专家系统公司）；University of Edinburgh（爱丁堡大学）
Benchmarking Gender and Political Bias in Large Language Models
School of Computing & Information Systems, The University of Melbourne（墨尔本大学计算与信息系统学院）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）
Statistical Properties of European Languages and Voynich Manuscript Analysis
Peoples’ Friendship University of Russia（俄罗斯人民友谊大学）；Keldysh Institute of Applied Mathematics of RAS（俄罗斯科学院凯尔迪什应用数学研究所）；Moscow Institute of Physics and Technology（莫斯科物理技术学院）
Financial University of Russia（俄罗斯联邦政府财政金融大学）；MEPhI（莫斯科国立核研究大学）；University Politehnica of Bucharest（布加勒斯特理工大学）；University of Szeged（塞格德大学）；Notre Dame College, Dhaka（达卡圣母学院）；Mozaik Education（Mozaik教育）
Making Metadata Fit for Next Generation Language Technology Platforms: The Metadata Schema of the European Language Grid
ILSP/Athena RC（雅典娜研究中心语言与语音处理研究所）；DFKI GmbH（德国人工智能研究中心）；Evaluations and Language Resources Distribution Agency (ELDA)（评估与语言资源分发局）；SAIL LABS Technology GmbH（SAIL LABS技术有限公司）；Expert System Iberia SL（伊比利亚专家系统公司）
FAME-MT Dataset: Formality Awareness Made Easy for Machine Translation Purposes
Laniqo（拉尼科公司）；Faculty of Computing and Telecommunications, Poznań University of Technology（波兹南理工大学计算与通信学院）；Faculty of Mathematics and Computer Science, Adam Mickiewicz University（亚当·密茨凯维奇大学数学与计算机科学学院）
