no code implementations • NLP4ConvAI (ACL) 2022 • Katharina Kann, Abteen Ebrahimi, Joewie Koh, Shiran Dudy, Alessandro Roncone
Human–computer conversation has long been an interest of artificial intelligence and natural language processing research.
no code implementations • NAACL (AmericasNLP) 2021 • Manuel Mager, Arturo Oncevay, Abteen Ebrahimi, John Ortega, Annette Rios, Angela Fan, Ximena Gutierrez-Vasques, Luis Chiruzzo, Gustavo Giménez-Lugo, Ricardo Ramos, Ivan Vladimir Meza Ruiz, Rolando Coto-Solano, Alexis Palmer, Elisabeth Mager-Hois, Vishrav Chaudhary, Graham Neubig, Ngoc Thang Vu, Katharina Kann
This paper presents the results of the 2021 Shared Task on Open Machine Translation for Indigenous Languages of the Americas.
no code implementations • FieldMatters (COLING) 2022 • Katharina Kann, Abteen Ebrahimi, Kristine Stenzel, Alexis Palmer
This translation task is challenging for multiple reasons: (1) the data is out-of-domain with respect to the MT system’s training data, (2) much of the data is conversational, (3) existing translations include non-standard and uncommon expressions, often reflecting properties of the documented language, and (4) the data includes borrowings from other regional languages.
no code implementations • 27 Mar 2024 • Abteen Ebrahimi, Kenneth Church
English has long been assumed the $\textit{lingua franca}$ of scientific research, and this notion is reflected in the natural language processing (NLP) research involving scientific document representation.
1 code implementation • 15 Feb 2023 • Abteen Ebrahimi, Arya D. McCarthy, Arturo Oncevay, Luis Chiruzzo, John E. Ortega, Gustavo A. Giménez-Lugo, Rolando Coto-Solano, Katharina Kann
However, the languages most in need of automatic alignment are low-resource and, thus, not typically included in the pretraining data.
no code implementations • ACL 2021 • Abteen Ebrahimi, Katharina Kann
Pretrained multilingual models (PMMs) enable zero-shot learning via cross-lingual transfer, performing best for languages seen during pretraining.
1 code implementation • ACL 2022 • Abteen Ebrahimi, Manuel Mager, Arturo Oncevay, Vishrav Chaudhary, Luis Chiruzzo, Angela Fan, John Ortega, Ricardo Ramos, Annette Rios, Ivan Meza-Ruiz, Gustavo A. Giménez-Lugo, Elisabeth Mager, Graham Neubig, Alexis Palmer, Rolando Coto-Solano, Ngoc Thang Vu, Katharina Kann
Continued pretraining offers improvements, with an average accuracy of 44. 05%.
no code implementations • 21 Nov 2020 • Vrindavan Harrison, Juraj Juraska, Wen Cui, Lena Reed, Kevin K. Bowden, Jiaqi Wu, Brian Schwarzmann, Abteen Ebrahimi, Rishi Rajasekaran, Nikhil Varghese, Max Wechsler-Azen, Steve Whittaker, Jeffrey Flanigan, Marilyn Walker
This report describes Athena, a dialogue system for spoken conversation on popular topics and current events.
no code implementations • ACL 2019 • Shereen Oraby, Vrindavan Harrison, Abteen Ebrahimi, Marilyn Walker
Neural natural language generation (NNLG) from structured meaning representations has become increasingly popular in recent years.