Papers by Nikita Semenov
RuPAWS: A Russian Adversarial Dataset for Paraphrase Identification (2022.lrec-1)
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Nikita Martynov, Irina Krotova, Varvara Logacheva, Alexander Panchenko, Olga Kozlova, Nikita Semenov
| Challenge: | Existing datasets for paraphrase identification lack challenging sentence pairs with high word overlap. |
| Approach: | They propose to use a dataset for Russian paraphrase detection that includes examples from PAWS translated to the Russian language and manually annotated by native speakers. |
| Outcome: | The proposed model performs well on both datasets while maintaining accuracy on the ParaPhraser benchmark. |
Text Detoxification using Large Pre-trained Neural Models (2021.emnlp-main)
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David Dale, Anton Voronov, Daryna Dementieva, Varvara Logacheva, Olga Kozlova, Nikita Semenov, Alexander Panchenko
| Challenge: | Existing studies on text detoxification cast this task as style transfer . text detox requires better preservation of the original meaning, authors argue . |
| Approach: | They propose two unsupervised methods for eliminating toxicity in text . they use a paraphraser guided by style-trained language models to keep the text content . |
| Outcome: | The proposed methods yield new SOTA results. |
ParaDetox: Detoxification with Parallel Data (2022.acl-long)
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Varvara Logacheva, Daryna Dementieva, Sergey Ustyantsev, Daniil Moskovskiy, David Dale, Irina Krotova, Nikita Semenov, Alexander Panchenko
| Challenge: | a pipeline for the collection of parallel data for the detoxification task is available. |
| Approach: | They propose a pipeline for the collection of parallel data for the detoxification task . they collect non-toxic paraphrases for over 10,000 English toxic sentences . |
| Outcome: | The proposed pipeline outperforms state-of-the-art models on both automatic and manual evaluations. |