Zobrazeno 1 - 10
of 97
pro vyhledávání: '"Jordan Boyd-Graber"'
Autor:
Quynh C Nguyen, Elizabeth M Aparicio, Michelle Jasczynski, Amara Channell Doig, Xiaohe Yue, Heran Mane, Neha Srikanth, Francia Ximena Marin Gutierrez, Nataly Delcid, Xin He, Jordan Boyd-Graber
Publikováno v:
JMIR Formative Research, Vol 8, p e51361 (2024)
BackgroundStark disparities exist in maternal and child outcomes and there is a need to provide timely and accurate health information. ObjectiveIn this pilot study, we assessed the feasibility and acceptability of a health chatbot for new mothers o
Externí odkaz:
https://doaj.org/article/e8832378b60f4e219811c878cda94f1f
Autor:
Dasha Pruss, Yoshinari Fujinuma, Ashlynn R Daughton, Michael J Paul, Brad Arnot, Danielle Albers Szafir, Jordan Boyd-Graber
Publikováno v:
PLoS ONE, Vol 14, Iss 5, p e0216922 (2019)
This work examines Twitter discussion surrounding the 2015 outbreak of Zika, a virus that is most often mild but has been associated with serious birth defects and neurological syndromes. We introduce and analyze a collection of 3.9 million tweets me
Externí odkaz:
https://doaj.org/article/2912c455711749f2a7447df49eae057a
This paper develops automatic song translation (AST) for tonal languages and addresses the unique challenge of aligning words' tones with melody of a song in addition to conveying the original meaning. We propose three criteria for effective AST -- p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e862a9f888a286475ea38f842df1f1a6
http://arxiv.org/abs/2203.13420
http://arxiv.org/abs/2203.13420
Autor:
Jordan Boyd-Graber, Samuel Carton, Shi Feng, Q. Vera Liao, Tania Lombrozo, Alison Smith-Renner, Chenhao Tan
Publikováno v:
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Tutorial Abstracts.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6f441d6bb7e52c569bdf8e661c2cbfcc
https://doi.org/10.18653/v1/2022.naacl-tutorials.4
https://doi.org/10.18653/v1/2022.naacl-tutorials.4
We introduce DELFT, a factoid question answering system which combines the nuance and depth of knowledge graph question answering approaches with the broader coverage of free-text. DELFT builds a free-text knowledge graph from Wikipedia, with entitie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ea96d83c1ad0b235ec2720e563e7420
http://arxiv.org/abs/2103.12876
http://arxiv.org/abs/2103.12876
Publikováno v:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dd90d4e396b710f76e28d9627fa92671
https://doi.org/10.18653/v1/2021.emnlp-main.444
https://doi.org/10.18653/v1/2021.emnlp-main.444
Publikováno v:
Proceedings of the 3rd Workshop on Machine Reading for Question Answering.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efec2f9e0f0322116178947d876a4cb4
https://doi.org/10.18653/v1/2021.mrqa-1.9
https://doi.org/10.18653/v1/2021.mrqa-1.9
Autor:
Jordan Boyd-Graber, Jannis Bulian, Bhuwan Dhingra, Benjamin Börschinger, Julian Martin Eisenschlos
Publikováno v:
NAACL-HLT
We release FoolMeTwice (FM2 for short), a large dataset of challenging entailment pairs collected through a fun multi-player game. Gamification encourages adversarial examples, drastically lowering the number of examples that can be solved using "sho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d2ea5eed83b0e046268001f52236f5f
https://doi.org/10.18653/v1/2021.naacl-main.32
https://doi.org/10.18653/v1/2021.naacl-main.32
Publikováno v:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b230ea0f3ac2e1b23c1442f915bcb9de
https://doi.org/10.18653/v1/2021.emnlp-main.756
https://doi.org/10.18653/v1/2021.emnlp-main.756
Autor:
Pedro Rodriguez, Jordan Boyd-Graber
Publikováno v:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7bc1e8d48249cb89d1508a34eaaa0144
https://doi.org/10.18653/v1/2021.emnlp-main.758
https://doi.org/10.18653/v1/2021.emnlp-main.758