Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Edoardo Barba"'
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:11156-11164
Enabling computers to comprehend the intent of human actions by processing language is one of the fundamental goals of Natural Language Understanding. An emerging task in this context is that of free-form event process typing, which aims at understan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3ffe3351f93982ef3c50eab76de1529
https://doi.org/10.1609/aaai.v36i10.21365
https://doi.org/10.1609/aaai.v36i10.21365
Publikováno v:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a5fd7d818931d5fc5d3e551ea2eb644
https://doi.org/10.18653/v1/2022.acl-long.177
https://doi.org/10.18653/v1/2022.acl-long.177
Publikováno v:
IJCAI
Scopus-Elsevier
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21)
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
Scopus-Elsevier
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21)
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
Word Sense Disambiguation (WSD), i.e., the task of assigning senses to words in context, has seen a surge of interest with the advent of neural models and a considerable increase in performance up to 80% F1 in English. However, when considering other
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21a2c06f600e478a6000ee7700ee5524
https://doi.org/10.24963/ijcai.2021/539
https://doi.org/10.24963/ijcai.2021/539
Publikováno v:
Scopus-Elsevier
Proc. of IJCAI 2021
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
IJCAI
Proc. of IJCAI 2021
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
IJCAI
Recently, generative approaches have been used effectively to provide definitions of words in their context. However, the opposite, i.e., generating a usage example given one or more words along with their definitions, has not yet been investigated.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::399a05197aa3538b3da5faa773f70cde
http://hdl.handle.net/11573/1604134
http://hdl.handle.net/11573/1604134
Publikováno v:
NAACL-HLT
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Word Sense Disambiguation (WSD) is a historical NLP task aimed at linking words in contexts to discrete sense inventories and it is usually cast as a multi-label classification task. Recently, several neural approaches have employed sense definitions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c55ecb4e172434e98304c2f6fc010fa4
http://hdl.handle.net/11573/1585586
http://hdl.handle.net/11573/1585586
Publikováno v:
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Scopus-Elsevier
IJCAI
Scopus-Elsevier
IJCAI
The knowledge acquisition bottleneck strongly affects the creation of multilingual sense-annotated data, hence limiting the power of supervised systems when applied to multilingual Word Sense Disambiguation. In this paper, we propose a semi-supervise
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9f475412680fc71ca10123c572fa7c3