Sławomir Dadas, Michał Perełkiewicz, Rafał Poświata
2020 W: TWELFTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, May 11-16 , 2020, PALAIS DU PHARO, Marseille, France : CONFERENCE PROCEEDINGS / Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis; Marseille: European Language Resources Association, s. 1674-1680
12th Language Resources and Evaluation Conference. Marsylia, 2020-05-11 - 2020-05-16
Methods for learning sentence representations have been actively developed in recent years. However, the lack of pre-trained models and datasets annotated at the sentence level has been a problem for low-resource languages such as Polish which led to less interest in applying these methods to language-specific tasks. In this study, we introduce two new Polish datasets for evaluating sentence embeddings and provide a comprehensive evaluation of eight sentence representation methods including Polish and multilingual models. We consider classic word embedding models, recently developed contextual embeddings and multilingual sentence encoders, showing strengths and weaknesses of specific approaches. We also examine different methods of aggregating word vectors into a single sentence vector.