Making sense of word embeddings M Pelevina, N Arefyev, C Biemann, A Panchenko arXiv preprint arXiv:1708.03390, 2017 | 176 | 2017 |
Human and Machine Judgements about Russian Semantic Relatedness A Panchenko, D Ustalov, N Arefyev, D Paperno, N Konstantinovam, ... Proceedings of the 5th Conference on Analysis of Images, Social Networks and …, 2016 | 81 | 2016 |
RUSSE'2018: a shared task on word sense induction for the Russian language A Panchenko, A Lopukhina, D Ustalov, K Lopukhin, N Arefyev, ... arXiv preprint arXiv:1803.05795, 2018 | 53 | 2018 |
Negative sampling improves hypernymy extraction based on projection learning D Ustalov, N Arefyev, C Biemann, A Panchenko arXiv preprint arXiv:1707.03903, 2017 | 36 | 2017 |
Always Keep your Target in Mind: Studying Semantics and Improving Performance of Neural Lexical Substitution N Arefyev, B Sheludko, A Podolskiy, A Panchenko Proceedings of the 28th International Conference on Computational …, 2020 | 35 | 2020 |
Evaluating three corpus-based semantic similarity systems for Russian P AI, L OO Dialog 28, 2015 | 35 | 2015 |
Neural granny at semeval-2019 task 2: A combined approach for better modeling of semantic relationships in semantic frame induction N Arefyev, B Sheludko, A Davletov, D Kharchev, A Nevidomsky, ... Proceedings of the 13th international workshop on semantic evaluation, 31-38, 2019 | 23 | 2019 |
HHMM at SemEval-2019 task 2: Unsupervised frame induction using contextualized word embeddings S Anwar, D Ustalov, N Arefyev, SP Ponzetto, C Biemann, A Panchenko arXiv preprint arXiv:1905.01739, 2019 | 21 | 2019 |
How much does a word weigh? Weighting word embeddings for word sense induction N Arefyev, P Ermolaev, A Panchenko arXiv preprint arXiv:1805.09209, 2018 | 20 | 2018 |
GlossReader at LSCDiscovery: Train to Select a Proper Gloss in English–Discover Lexical Semantic Change in Spanish M Rachinskiy, N Arefyev Proceedings of the 3rd Workshop on Computational Approaches to Historical …, 2022 | 17 | 2022 |
BOS at SemEval-2020 task 1: Word sense induction via lexical substitution for lexical semantic change detection N Arefyev, V Zhikov Proceedings of the Fourteenth Workshop on Semantic Evaluation, 171-179, 2020 | 15 | 2020 |
A comparative study of lexical substitution approaches based on neural language models N Arefyev, B Sheludko, A Podolskiy, A Panchenko arXiv preprint arXiv:2006.00031, 2020 | 15 | 2020 |
Combining lexical substitutes in neural word sense induction N Arefyev, B Sheludko, A Panchenko Proceedings of the International Conference on Recent Advances in Natural …, 2019 | 12 | 2019 |
The document vectors using cosine similarity revisited Z Bingyu, N Arefyev arXiv preprint arXiv:2205.13357, 2022 | 11 | 2022 |
Deepmistake: Which senses are hard to distinguish for a wordincontext model N Arefyev, D Homskiy, M Fedoseev, A Davletov, V Protasov, A Panchenko Computational linguistics and intellectual technologies: Papers from the …, 2021 | 11 | 2021 |
Word2vec not dead: predicting hypernyms of co-hyponyms is better than reading definitions NV Arefyev, MV Fedoseev, AV Kabanov, VS Zizov Computational Linguistics and Intellectual Technologies, 13-32, 2020 | 11 | 2020 |
LIORI at SemEval-2021 task 8: Ask transformer for measurements A Davletov, D Gordeev, N Arefyev, E Davletov Proceedings of the 15th International Workshop on Semantic Evaluation …, 2021 | 10 | 2021 |
BOS at LSCDiscovery: Lexical Substitution for Interpretable Lexical Semantic Change Detection A Kudisov, N Arefyev Proceedings of the 3rd Workshop on Computational Approaches to Historical …, 2022 | 9 | 2022 |
Nb-mlm: Efficient domain adaptation of masked language models for sentiment analysis N Arefyev, D Kharchev, A Shelmanov Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 8 | 2021 |
Zeroshot crosslingual transfer of a gloss language model for semantic change detection M Rachinskiy, N Arefyev Computational linguistics and intellectual technologies: Papers from the …, 2021 | 8 | 2021 |