# Sentence Embeddings for Russian NLU

Source: [Sentence Embeddings for Russian NLU](<https://www.sota2.com/research/paper/68fa66921e209131cea10f9f>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T21:53:21.106Z

Authors: Dmitry Popov, Alexander Pugachev, Polina Svyatokum, Elizaveta Svitanko, Ekaterina Artemova

Published: 2019-10-29T14:28:34.000Z

## Abstract

We investigate the performance of sentence embeddings models on several tasks for the Russian language. In our comparison, we include such tasks as multiple choice question answering, next sentence prediction, and paraphrase identification. We employ FastText embeddings as a baseline and compare it to ELMo and BERT embeddings. We conduct two series of experiments, using both unsupervised (i.e., based on similarity measure only) and supervised approaches for the tasks. Finally, we present datasets for multiple choice question answering and next sentence prediction in Russian.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1910.13291>)

[PDF](<https://arxiv.org/pdf/1910.13291.pdf>)