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The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021 (5)
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Simple Search
Hits 1 – 9 of 9
1
RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Barikeri, Soumya
;
Glavaš, Goran
. - : Underline Science Inc., 2021
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2
How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
., Iryna
;
., Sebastian
. - : Underline Science Inc., 2021
BASE
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3
Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
., Nigel
;
Korhonen, Anna
. - : Underline Science Inc., 2021
BASE
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4
LexFit: Lexical Fine-Tuning of Pretrained Language Models ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Glavaš, Goran
;
Korhonen, Anna
. - : Underline Science Inc., 2021
BASE
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5
A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
., Hinrich
;
Korhonen, Anna
. - : Underline Science Inc., 2021
BASE
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6
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity
Vulic, Ivan
;
Baker, Simon
;
Ponti, Edoardo Maria
;
Petti, Ulla
;
Leviant, Ira
;
Wing, Kelly
;
Majewska, Olga
;
Bar, Eden
;
Malone, Matt
;
Poibeau, Thierry
;
Reichart, Roi
;
Korhonen, Anna
In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02975786 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2020, 46 (4), pp.847-897 ; https://direct.mit.edu/coli/article/46/4/847/97326/Multi-SimLex-A-Large-Scale-Evaluation-of (2020)
Abstract:
Données et informations liées à la publication : https://multisimlex.com/ ; International audience ; We introduce Multi-SimLex, a large-scale lexical resource and evaluation benchmark covering datasets for 12 typologically diverse languages, including major languages (e.g., Mandarin Chinese, Spanish, Russian) as well as less-resourced ones (e.g., Welsh, Kiswahili). Each language dataset is annotated for the lexical relation of semantic similarity and contains 1,888 semantically aligned concept pairs, providing a representative coverage of word classes (nouns, verbs, adjectives, adverbs), frequency ranks, similarity intervals, lexical fields, and concreteness levels. Additionally, owing to the alignment of concepts across languages, we provide a suite of 66 cross-lingual semantic similarity datasets. Due to its extensive size and language coverage, Multi-SimLex provides entirely novel opportunities for experimental evaluation and analysis. On its monolingual and cross-lingual benchmarks, we evaluate and analyze a wide array of recent state-of-the-art monolingual and cross-lingual representation models, including static and contextualized word embeddings (such as fastText, M-BERT and XLM), externally informed lexical representations, as well as fully unsupervised and (weakly) supervised cross-lingual word embeddings. We also present a step-by-step dataset creation protocol for creating consistent, Multi-Simlex-style resources for additional languages. We make these contributions -- the public release of Multi-SimLex datasets, their creation protocol, strong baseline results, and in-depth analyses which can be be helpful in guiding future developments in multilingual lexical semantics and representation learning -- available via a website which will encourage community effort in further expansion of Multi-Simlex to many more languages. Such a large-scale semantic resource could inspire significant further advances in NLP across languages.
Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
;
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]
;
[INFO.INFO-TT]Computer Science [cs]/Document and Text Processing
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[SCCO.COMP]Cognitive science/Computer science
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[SCCO.LING]Cognitive science/Linguistics
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[SHS.INFO]Humanities and Social Sciences/Library and information sciences
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[SHS.LANGUE]Humanities and Social Sciences/Linguistics
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[SHS.STAT]Humanities and Social Sciences/Methods and statistics
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Lexicon
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Linguistic Resource
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Multilinguality
;
Semantics
;
Typology
URL:
https://hal.archives-ouvertes.fr/hal-02975786/file/coli_a_00391.pdf
https://hal.archives-ouvertes.fr/hal-02975786
https://hal.archives-ouvertes.fr/hal-02975786/document
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7
A deep learning approach to bilingual lexicon induction in the biomedical domain. ...
Heyman, Geert
;
Vulić, Ivan
;
Moens, Marie-Francine
. - : Apollo - University of Cambridge Repository, 2018
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8
A deep learning approach to bilingual lexicon induction in the biomedical domain.
Heyman, Geert
;
Vulić, Ivan
;
Moens, Marie-Francine
. - : Springer Science and Business Media LLC, 2018. : BMC Bioinformatics, 2018
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9
Bio-SimVerb and Bio-SimLex: wide-coverage evaluation sets of word similarity in biomedicine.
Chiu, Billy
;
Pyysalo, Sampo
;
Vulić, Ivan
. - : BioMed Central, 2018. : BMC bioinformatics, 2018
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