Zero-shot cross-lingual dependency parsing through contextual embedding transformation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10440973" target="_blank" >RIV/00216208:11320/21:10440973 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Zero-shot cross-lingual dependency parsing through contextual embedding transformation
Original language description
Linear embedding transformation has been shown to be effective for zero-shot cross-lingual transfer tasks and achieve surprisingly promising results. However, cross-lingual embedding space mapping is usually studied in static word-level embeddings, where a space transformation is derived by aligning representations of translation pairs that are referred from dictionaries. We move further from this line and investigate a contextual embedding alignment approach which is sense-level and dictionary-free. To enhance the quality of the mapping, we also provide a deep view of properties of contextual embeddings, i.e., the anisotropy problem and its solution. Experiments on zero-shot dependency parsing through the concept-shared space built by our embedding transformation substantially outperform state-of-the-art methods using multilingual embeddings.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Adapt-NLP 2021 - 2nd Workshop on Domain Adaptation for NLP, Proceedings
ISBN
978-1-954085-08-4
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
204-213
Publisher name
Association for Computational Linguistics
Place of publication
Stroudsburg
Event location
online
Event date
Apr 20, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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