Macular: A Multi-Task Adversarial Framework for Cross-Lingual Natural Language Understanding
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AQJ4PIY6M" target="_blank" >RIV/00216208:11320/23:QJ4PIY6M - isvavai.cz</a>
Result on the web
<a href="https://dl.acm.org/doi/10.1145/3580305.3599864" target="_blank" >https://dl.acm.org/doi/10.1145/3580305.3599864</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3580305.3599864" target="_blank" >10.1145/3580305.3599864</a>
Alternative languages
Result language
angličtina
Original language name
Macular: A Multi-Task Adversarial Framework for Cross-Lingual Natural Language Understanding
Original language description
"Cross-lingual natural language understanding~(NLU) aims to train NLU models on a source language and apply the models to NLU tasks in target languages, and is a fundamental task for many cross-language applications."
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
—
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"
ISBN
9798400701030
ISSN
—
e-ISSN
—
Number of pages
10
Pages from-to
5061-5070
Publisher name
ACM
Place of publication
Long Beach CA USA
Event location
Long Beach CA USA
Event date
Jan 1, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—