Charting the European LLM Benchmarking Landscape: A New Taxonomy and a Set of Best Practices
Not on the map. Why?
Abstract (arXiv)
While new benchmarks for large language models (LLMs) are being developed continuously to catch up with the growing capabilities of new models and AI in general, using and evaluating LLMs in non-English languages remains a little-charted landscape. We give a concise overview of recent developments in LLM benchmarking, and then propose a new taxonomy for the categorization of benchmarks that is tailored to multilingual or non-English use scenarios. We further propose a set of best practices and quality standards that could lead to a more coordinated development of benchmarks for European languages. Among other recommendations, we advocate for a higher language and culture sensitivity of evaluation methods.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 42 of its 69 references that are in the map. First posted on arXiv 28 Oct 2025.
Builds on
42 of 69 references.
References · 42
- 2020Measuring Massive Multitask Language Understandingcited by 7,963
- 2018Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challengecited by 4,886
- 2019HellaSwag: Can a Machine Really Finish Your Sentence?cited by 4,100
- 2021TruthfulQA: Measuring How Models Mimic Human Falsehoodscited by 2,975
- 2019BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questionscited by 2,183
- 2022Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelscited by 1,998
- 2019Language Models as Knowledge Bases?cited by 1,936
- 2024MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmarkcited by 1,848
- 2019SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systemscited by 1,729
- 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,356
- 2018Neural Network Acceptability Judgmentscited by 958
- 2016Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyondcited by 812
30 more
- 2021SUPERB: Speech processing Universal PERformance Benchmarkcited by 666
- 2019BLiMP: The Benchmark of Linguistic Minimal Pairs for Englishcited by 564
- 2021The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translationcited by 560
- 2023DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Modelscited by 518
- 2022FLEURS: Few-shot Learning Evaluation of Universal Representations of Speechcited by 469
- 2018Gender Bias in Coreference Resolutioncited by 442
- 2019Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classificationcited by 404
- 2018WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representationscited by 372
- 2020XCOPA: A Multilingual Dataset for Causal Commonsense Reasoningcited by 333
- 2023The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variantscited by 311
- 2024LiveBench: A Challenging, Contamination-Limited LLM Benchmarkcited by 262
- 2018Dear Sir or Madam, May I introduce the GYAFC Dataset: Corpus, Benchmarks and Metrics for Formality Style Transfercited by 211
- 2023Evaluating Large Language Models: A Comprehensive Surveycited by 202
- 2018ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehensioncited by 200
- 2019BillSum: A Corpus for Automatic Summarization of US Legislationcited by 117
- 2013A Computational Approach to Politeness with Application to Social Factorscited by 106
- 2024A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendationscited by 85
- 2025MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluationcited by 79
- 2023ML-SUPERB: Multilingual Speech Universal PERformance Benchmarkcited by 71
- 2024DIALECTBENCH: A NLP Benchmark for Dialects, Varieties, and Closely-Related Languagescited by 50
- 2024Beyond English-Centric LLMs: What Language Do Multilingual Language Models Think in?cited by 41
- 2025A Survey on Large Language Model Benchmarkscited by 36
- 2024mHumanEval -- A Multilingual Benchmark to Evaluate Large Language Models for Code Generationcited by 32
- 2024BertaQA: How Much Do Language Models Know About Local Culture?cited by 23
- 2021BERTi'c -- The Transformer Language Model for Bosnian, Croatian, Montenegrin and Serbiancited by 21
- 2024BenCzechMark : A Czech-centric Multitask and Multimetric Benchmark for Large Language Models with Duel Scoring Mechanismcited by 12
- 2025Who Benchmarks the Benchmarks? Towards Comprehensive Evaluation of Commonsense Reasoning Benchmarkscited by 11
- 2025Evaluating Polish linguistic and cultural competency in large language modelscited by 6
- 2025IberBench: LLM Evaluation on Iberian Languagescited by 5
- 2025CUS-QA: Local-Knowledge-Oriented Open-Ended Question Answering Datasetcited by 4
Built on by
Citing papers per year: 2026: 1.
1 paper.