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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 3 4 5 6 Hits 41 – 60 of 115 41 SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ... The 28th International Conference on Computational Linguistics 2020; Glavaš, Goran; Korhonen, Anna. - : Underline Science Inc., 2020 BASE Show details 42 Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ... The 28th International Conference on Computational Linguistics 2020; Glavaš, Goran; Korhonen, Anna. - : Underline Science Inc., 2020 BASE Show details 43 Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ... Lauscher, Anne; Vulic, Ivan; Ponti, Edoardo. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 44 Classification-Based Self-Learning for Weakly Supervised Bilingual Lexicon Induction ... Karan, Mladen; Vulic, Ivan; Korhonen, Anna. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 45 Improving Bilingual Lexicon Induction with Unsupervised Post-Processing of Monolingual Word Vector Spaces ... Vulic, Ivan; Korhonen, Anna; Glavas, Goran. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 46 Improving Bilingual Lexicon Induction with Unsupervised Post-Processing of Monolingual Word Vector Spaces Vulic, Ivan; Korhonen, Anna; Glavas, Goran. - : 5TH WORKSHOP ON REPRESENTATION LEARNING FOR NLP (REPL4NLP-2020), 2020 BASE Show details 47 Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity Lauscher, Anne; Vulic, Ivan; Ponti, Edoardo. - : International Committee on Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.coling-main.118, 2020. : Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), 2020 BASE Show details 48 Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis Majewska, Olga; Vulic, Ivan; McCarthy, Diana. - : International Committee on Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.coling-main.423, 2020. : Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), 2020 BASE Show details 49 Classification-Based Self-Learning for Weakly Supervised Bilingual Lexicon Induction Karan, Mladen; Vulic, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2020 BASE Show details 50 Emergent Communication Pretraining for Few-Shot Machine Translation Vulic, Ivan; Ponti, Edoardo; Korhonen, Anna. - : International Committee on Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.coling-main.416, 2020. : Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), 2020 BASE Show details 51 Multidirectional Associative Optimization of Function-Specific Word Representations Gerz, Daniela; Vulic, Ivan; Rei, Marek. - : Association for Computational Linguistics, 2020. : 58TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2020), 2020 BASE Show details 52 A systematic literature review of automatic Alzheimer’s disease detection from speech and language Petti, Ulla; Baker, Simon; Korhonen, Anna In: J Am Med Inform Assoc (2020) BASE Show details 53 Specializing unsupervised pretraining models for word-level semantic similarity Ponti, Edoardo Maria; Korhonen, Anna; Vulić, Ivan. - : Association for Computational Linguistics, ACL, 2020 BASE Show details 54 Classification-based self-learning for weakly supervised bilingual lexicon induction Vulić, Ivan; Korhonen, Anna; Glavaš, Goran. - : Association for Computational Linguistics, 2020 BASE Show details 55 Probing pretrained language models for lexical semantics Vulić, Ivan; Korhonen, Anna; Litschko, Robert. - : Association for Computational Linguistics, 2020 BASE Show details 56 XCOPA: A multilingual dataset for causal commonsense reasoning Ponti, Edoardo Maria; Majewska, Olga; Liu, Qianchu. - : Association for Computational Linguistics, 2020 BASE Show details 57 Improving bilingual lexicon induction with unsupervised post-processing of monolingual word vector spaces Glavaš, Goran; Korhonen, Anna; Vulić, Ivan. - : Association for Computational Linguistics, 2020 BASE Show details 58 SemEval-2020 Task 2: Predicting multilingual and cross-lingual (graded) lexical entailment Glavaš, Goran; Vulić, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2020 BASE Show details 59 Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing Ponti, Edoardo Maria; O’Horan, Helen; Berzak, Yevgeni; Vulić, Ivan; Reichart, Roi; Poibeau, Thierry; Shutova, Ekaterina; Korhonen, Anna In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02425462 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2019, 45 (3), pp.559-601. ⟨10.1162/coli_a_00357⟩ ; https://www.mitpressjournals.org/doi/abs/10.1162/coli_a_00357 (2019) Abstract: International audience ; Linguistic typology aims to capture structural and semantic variation across the world’s languages. A large-scale typology could provide excellent guidance for multilingual Natural Language Processing (NLP), particularly for languages that suffer from the lack of human labeled resources. We present an extensive literature survey on the use of typological information in the development of NLP techniques. Our survey demonstrates that to date, the use of information in existing typological databases has resulted in consistent but modest improvements in system performance. We show that this is due to both intrinsic limitations of databases (in terms of coverage and feature granularity) and under-utilization of the typological features included in them. We advocate for a new approach that adapts the broad and discrete nature of typological categories to the contextual and continuous nature of machine learning algorithms used in contemporary NLP. In particular, we suggest that such an approach could be facilitated by recent developments in data-driven induction of typological knowledge. Keyword: [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; [SCCO.COMP]Cognitive science/Computer science; [SCCO.LING]Cognitive science/Linguistics; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; [SHS.STAT]Humanities and Social Sciences/Methods and statistics; Computational linguistics; Typology URL: https://hal.archives-ouvertes.fr/hal-02425462 https://hal.archives-ouvertes.fr/hal-02425462/file/coli_a_00357-Ponti.pdf https://hal.archives-ouvertes.fr/hal-02425462/document https://doi.org/10.1162/coli_a_00357 BASE Hide details 60 Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ... Lauscher, Anne; Vulić, Ivan; Ponti, Edoardo Maria. - : arXiv, 2019 BASE Show details Page: 1 2 3 4 5 6

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