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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 1 – 20 of 23 1 Active Learning for Sequence Tagging with Deep Pre-trained Models and Bayesian Uncertainty Estimates ... Shelmanov, Artem; Puzyrev, Dmitri; Kupriyanova, Lyubov. - : arXiv, 2021 BASE Show details 2 RUSSE'2020: Findings of the First Taxonomy Enrichment Task for the Russian language ... Nikishina, Irina; Logacheva, Varvara; Panchenko, Alexander. - : arXiv, 2020 BASE Show details 3 Word Sense Disambiguation for 158 Languages using Word Embeddings Only ... Logacheva, Varvara; Teslenko, Denis; Shelmanov, Artem. - : arXiv, 2020 BASE Show details 4 Studying Taxonomy Enrichment on Diachronic WordNet Versions ... Nikishina, Irina; Panchenko, Alexander; Logacheva, Varvara. - : arXiv, 2020 BASE Show details 5 A Comparative Study of Lexical Substitution Approaches based on Neural Language Models ... Arefyev, Nikolay; Sheludko, Boris; Podolskiy, Alexander; Panchenko, Alexander. - : arXiv, 2020 Abstract: Lexical substitution in context is an extremely powerful technology that can be used as a backbone of various NLP applications, such as word sense induction, lexical relation extraction, data augmentation, etc. In this paper, we present a large-scale comparative study of popular neural language and masked language models (LMs and MLMs), such as context2vec, ELMo, BERT, XLNet, applied to the task of lexical substitution. We show that already competitive results achieved by SOTA LMs/MLMs can be further improved if information about the target word is injected properly, and compare several target injection methods. In addition, we provide analysis of the types of semantic relations between the target and substitutes generated by different models providing insights into what kind of words are really generated or given by annotators as substitutes. ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2006.00031 https://dx.doi.org/10.48550/arxiv.2006.00031 BASE Hide details 6 Making Fast Graph-based Algorithms with Graph Metric Embeddings ... Kutuzov, Andrey; Dorgham, Mohammad; Oliynyk, Oleksiy. - : arXiv, 2019 BASE Show details 7 On the Compositionality Prediction of Noun Phrases using Poincaré Embeddings ... Jana, Abhik; Puzyrev, Dmitry; Panchenko, Alexander. - : arXiv, 2019 BASE Show details 8 Every child should have parents: a taxonomy refinement algorithm based on hyperbolic term embeddings ... Aly, Rami; Acharya, Shantanu; Ossa, Alexander. - : arXiv, 2019 BASE Show details 9 Hypernyms extracted from a large text corpus using Hearst lexical-syntactic patterns ... Panchenko, Alexander. - : Zenodo, 2019 BASE Show details 10 Hypernyms extracted from a large text corpus using Hearst lexical-syntactic patterns ... Panchenko, Alexander. - : Zenodo, 2019 BASE Show details 11 Datasets for Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction ... Ustalov, Dmitry; Panchenko, Alexander; Biemann, Chris. - : Zenodo, 2019 BASE Show details 12 Datasets for Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction ... Ustalov, Dmitry; Panchenko, Alexander; Biemann, Chris. - : Zenodo, 2019 BASE Show details 13 RUSSE'2018: A Shared Task on Word Sense Induction for the Russian Language ... Panchenko, Alexander; Lopukhina, Anastasiya; Ustalov, Dmitry. - : arXiv, 2018 BASE Show details 14 Sentiment Index of the Russian Speaking Facebook ... Panchenko, Alexander. - : arXiv, 2018 BASE Show details 15 How much does a word weigh? Weighting word embeddings for word sense induction ... Arefyev, Nikolay; Ermolaev, Pavel; Panchenko, Alexander. - : arXiv, 2018 BASE Show details 16 RUSSE: The First Workshop on Russian Semantic Similarity ... Panchenko, Alexander; Loukachevitch, Natalia; Ustalov, Dmitry. - : arXiv, 2018 BASE Show details 17 An Unsupervised Word Sense Disambiguation System for Under-Resourced Languages ... Ustalov, Dmitry; Teslenko, Denis; Panchenko, Alexander. - : arXiv, 2018 BASE Show details 18 Enriching Frame Representations with Distributionally Induced Senses ... Faralli, Stefano; Panchenko, Alexander; Biemann, Chris. - : arXiv, 2018 BASE Show details 19 Negative Sampling Improves Hypernymy Extraction Based on Projection Learning ... Ustalov, Dmitry; Arefyev, Nikolay; Panchenko, Alexander. - : Zenodo, 2017 BASE Show details 20 A Framework for Enriching Lexical Semantic Resources with Distributional Semantics ... Biemann, Chris; Faralli, Stefano; Panchenko, Alexander. - : arXiv, 2017 BASE Show details Page: 1 2

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