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Methods for learning sentence representations have been actively developed inrecent years. However, the lack of pre-trained models and datasets annotated atthe sentence level has been a problem for low-resource languages such as Polishwhich led to less interest in applying these methods to language-specifictasks. In this study, we introduce two new Polish datasets for evaluatingsentence embeddings and provide a comprehensive evaluation of eight sentencerepresentation methods including Polish and multilingual models. We considerclassic word embedding models, recently developed contextual embeddings andmultilingual sentence encoders, showing strengths and weaknesses of specificapproaches. We also examine different methods of aggregating word vectors intoa single sentence vector.

Evaluation of Sentence Representations in Polish