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We investigate the performance of sentence embeddings models on several tasksfor the Russian language. In our comparison, we include such tasks as multiplechoice question answering, next sentence prediction, and paraphraseidentification. We employ FastText embeddings as a baseline and compare it toELMo and BERT embeddings. We conduct two series of experiments, using bothunsupervised (i.e., based on similarity measure only) and supervised approachesfor the tasks. Finally, we present datasets for multiple choice questionanswering and next sentence prediction in Russian.

Sentence Embeddings for Russian NLU