Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Liscio, Enrico"'
Active Learning (AL) addresses the high costs of collecting human annotations by strategically annotating the most informative samples. However, for subjective NLP tasks, incorporating a wide range of perspectives in the annotation process is crucial
Externí odkaz:
http://arxiv.org/abs/2404.15720
Autor:
van der Meer, Michiel, Liscio, Enrico, Jonker, Catholijn M., Plaat, Aske, Vossen, Piek, Murukannaiah, Pradeep K.
Publikováno v:
Journal of Artificial Intelligence Research (JAIR), 80:1187-1222, 2024
Large-scale survey tools enable the collection of citizen feedback in opinion corpora. Extracting the key arguments from a large and noisy set of opinions helps in understanding the opinions quickly and accurately. Fully automated methods can extract
Externí odkaz:
http://arxiv.org/abs/2403.09713
Understanding citizens' values in participatory systems is crucial for citizen-centric policy-making. We envision a hybrid participatory system where participants make choices and provide motivations for those choices, and AI agents estimate their va
Externí odkaz:
http://arxiv.org/abs/2402.16751
Recent advances in NLP show that language models retain a discernible level of knowledge in deontological ethics and moral norms. However, existing works often treat morality as binary, ranging from right to wrong. This simplistic view does not captu
Externí odkaz:
http://arxiv.org/abs/2401.17228
Autor:
Lera-Leri, Roger X., Liscio, Enrico, Bistaffa, Filippo, Jonker, Catholijn M., Lopez-Sanchez, Maite, Murukannaiah, Pradeep K., Rodriguez-Aguilar, Juan A., Salas-Molina, Francisco
Publikováno v:
In Knowledge-Based Systems 5 March 2024 287
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
van der Meer, Michiel, Liscio, Enrico, Jonker, Catholijn M., Plaat, Aske, Vossen, Piek, Murukannaiah, Pradeep, Schlobach, Stefan, Pérez-Ortiz, María, Tielman, Myrthe
Publikováno v:
HHAI2022: Augmenting Human Intellect: Proceedings of the First International Conference on Hybrid Human-Artificial Intelligence, 32-45
STARTPAGE=32;ENDPAGE=45;TITLE=HHAI2022: Augmenting Human Intellect
STARTPAGE=32;ENDPAGE=45;TITLE=HHAI2022: Augmenting Human Intellect
The key arguments underlying a large and noisy set of opinions help understand the opinions quickly and accurately. Fully automated methods can extract arguments but (1) require large labeled datasets and (2) work well for known viewpoints, but not f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=narcis______::2dd47168c85f365230d0d2ef1f51a193
https://research.vu.nl/en/publications/25624514-430a-48cb-a875-9ced9534200f
https://research.vu.nl/en/publications/25624514-430a-48cb-a875-9ced9534200f