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An Interpretable Approach to Lexical Semantic Change Detection with Lexical Substitution
P. 31–46.
Arefyev N.V., Bykov D. A.
Publication based on the results of:
In book
Issue 20: Основной том. , -, 2021.
Ryzhova A., Ryzhova D., Sochenkov I., , in: Computational Linguistics and Intellectual Technologies: Papers from the Annual International Conference “Dialogue” (2021)Issue 20: Основной том.: -, 2021. P. 597–606.
Added: October 30, 2021
Rachinskiy M., Arefyev N., , in: Computational Linguistics and Intellectual Technologies: Papers from the Annual International Conference “Dialogue” (2021)Issue 20: Основной том.: -, 2021. P. 578–586.
Added: September 23, 2021
Nikolay Arefyev, Fedoseev M., Protasov V. et al., , in: Computational Linguistics and Intellectual Technologies: Papers from the Annual International Conference “Dialogue” (2021)Issue 20: Основной том.: -, 2021. P. 16–30.
In this paper, we describe our solution of the Lexical Semantic Change Detection (LSCD) problem. It is based on a WordinContext (WiC) model detecting whether two occurrences of a particular word carry the same meaning. We propose and compare several WiC architectures and training schemes, and also different ways to convert WiC predictions into final ...
Added: September 23, 2021
Nikolay Arefyev, Zhikov V., , in: Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval-2020).: Association for Computational Linguistics, 2020. P. 171–179.
SemEval-2020 Task 1 is devoted to detection of changes in word meaning over time. The first subtask raises a question if a particular word has acquired or lost any of its senses during the given time period. The second subtask requires estimating the change in frequencies of the word senses. We have submitted two solutions ...
Added: December 7, 2020
Nikolay Arefyev, Sheludko B., Podolskiy A. et al., , in: Proceedings of the 28th International Conference on Computational Linguistics.: International Committee on Computational Linguistics, 2020. P. 1242–1255.
Lexical substitution, i.e. generation of plausible words that can replace a particular target word in a given context, is an extremely powerful technology that can be used as a backbone of various NLP applications, including word sense induction and disambiguation, lexical relation extraction, data augmentation, etc. In this paper, we present a large-scale comparative study ...
Added: December 7, 2020
Arefyev Nikolay, Sheludko B., Adis D. et al., , in: Proceedings of the 13th International Workshop on Semantic Evaluation (SemEval-2019).: Minneapolis: Association for Computational Linguistics, 2019. P. 31–38.
We describe our solutions for semantic frame and role induction subtasks of SemEval 2019 Task 2. Our approaches got the highest scores, and the solution for the frame induction problem officially took the first place. The main contributions of this paper are related to the semantic frame induction problem. We propose a combined approach that ...
Added: October 10, 2020
Anwar S., Ustalov D., Arefyev N. et al., , in: Proceedings of the 13th International Workshop on Semantic Evaluation (SemEval-2019).: Minneapolis: Association for Computational Linguistics, 2019. P. 125–129.
We present our system for semantic frame induction that showed the best performance in Subtask B.1 and finished as the runner-up in Subtask A of the SemEval 2019 Task 2 on unsupervised semantic frame induction (Qasem-iZadeh et al., 2019). Our approach separates this task into two independent steps: verb clustering using word and their context ...
Added: October 10, 2020
Panchenko A., Lopukhina A., Ustalov D. et al., , in: Computational Linguistics and Intellectual Technologies. International Conference "Dialogue 2018" Proceedings.: M.: Conference Proceedings Editorial board, 2018. P. 547–564.
The paper describes the results of the first shared task on word sense induction (WSI) for the Russian language. While similar shared tasks were conducted in the past for some Romance and Germanic languages, we explore the performance of sense induction and disambiguation methods for a Slavic language that shares many features with other Slavic ...
Added: October 9, 2020
Arefyev, N., Ermolaev P., Panchenko A., , in: Computational Linguistics and Intellectual Technologies. International Conference "Dialogue 2018" Proceedings.: M.: Conference Proceedings Editorial board, 2018. P. 68–84.
The paper describes our participation in the first shared task on word sense induction and disambiguation for the Russian language RUSSE'2018 [Panchenko et al., 2018]. For each of several dozens of ambiguous words, the participants were asked to group text fragments containing it according to the senses of this word, which were not provided beforehand, ...
Added: October 9, 2020
Struyanskiy O., Arefyev, N., , in: Supplementary Proceedings of the 7th International Conference on Analysis of Images, Social Networks and Texts (AIST-SUP 2018), Moscow, Russia, July 5-7, 2018.: Aachen: CEUR Workshop Proceedings, 2018. P. 208–213.
Attentional neural networks have achieved remarkable results for a number of tasks in the past few years. The fascinating success of neural networks with attention mechanism in natural language processing, especially in machine translation, suggests that these models can capture the meaning of ambiguous words considering their context. In this paper we introduce a new ...
Added: October 9, 2020
Arefyev, N, Boris S., Aleksashina T., , in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected PapersVol. 11832.: Cham: Springer, 2019. P. 105–121.
Word sense induction (WSI) is the problem of grouping occurrences of an ambiguous word according to the expressed sense of this word. Recently a new approach to this task was proposed, which generates possible substitutes for the ambiguous word in a particular context using neural language models, and then clusters sparse bag-of-words vectors built from ...
Added: October 9, 2020
Nikolay Arefyev, Boris S., Panchenko A., , in: Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2019.: INCOMA Ltd, 2019. P. 62–70.
Word Sense Induction (WSI) is the task of grouping of occurrences of an ambiguous word according to their meaning. In this work, we improve the approach to WSI proposed by Amrami and Goldberg (2018) based on clustering of lexical substitutes for an ambiguous word in a particular context obtained from neural language models. Namely, we ...
Added: October 9, 2020
Panchenko A., Lopukhina A., Ustalov D. et al., Компьютерная лингвистика и интеллектуальные технологии 2018 No. 17 P. 547–564
The paper describes the results of the first shared task on word sense induction (WSI) for the Russian language. While similar shared tasks were conducted in the past for some Romance and Germanic languages, we explore the performance of sense induction and disambiguation methods for a Slavic language that shares many features with other Slavic ...
Added: June 7, 2018
Лопухин К. А., Iomdin B., Lopukhina A., Компьютерная лингвистика и интеллектуальные технологии 2017 Vol. 1 No. 16 P. 121–134
The assumption that senses are mutually disjoint and have clear boundaries has been drawn into doubt by several linguists and psychologists. The problem of word sense granularity is widely discussed both in lexicographic and in NLP studies. We aim to study word senses in the wild—in raw corpora— by performing word sense induction (WSI). WSI ...
Added: September 27, 2017