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RussianSuperGLUE: A Russian Language Understanding Evaluation Benchmark

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arxiv 2010.15925 v2 pith:RYH6ZCV6 submitted 2020-10-29 cs.CL cs.AI

classification cs.CLcs.AI
keywords languagemodelsrussianbenchmarkevaluationfirstgeneralmethodology
verification ladder T0 review T1 audit T2 compute T3 formal
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In this paper, we introduce an advanced Russian general language understanding evaluation benchmark -- RussianGLUE. Recent advances in the field of universal language models and transformers require the development of a methodology for their broad diagnostics and testing for general intellectual skills - detection of natural language inference, commonsense reasoning, ability to perform simple logical operations regardless of text subject or lexicon. For the first time, a benchmark of nine tasks, collected and organized analogically to the SuperGLUE methodology, was developed from scratch for the Russian language. We provide baselines, human level evaluation, an open-source framework for evaluating models (https://github.com/RussianNLP/RussianSuperGLUE), and an overall leaderboard of transformer models for the Russian language. Besides, we present the first results of comparing multilingual models in the adapted diagnostic test set and offer the first steps to further expanding or assessing state-of-the-art models independently of language.

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  1. skLEP: A Slovak General Language Understanding Benchmark

    cs.CL 2025-06 conditional novelty 6.0 of 10

    A nine-task Slovak-language understanding benchmark with translated and newly curated datasets, plus the first broad fine-tuned model comparison for Slovak.

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