no code implementations • NAACL (AmericasNLP) 2021 • Delfino Zacarías Márquez, Ivan Vladimir Meza Ruiz
The proposed system is based on the Transformer neural architecture and it uses sub-word level tokenization as the input.
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 • NIDCP (LREC) 2022 • Carlos Daniel Hernandez Mena, Ivan Vladimir Meza Ruiz
This work presents the path toward the creation of eight Spoken Language Resources under the umbrella of the Mexican Social Service national program.
no code implementations • RANLP 2021 • Jessica López Espejel, Gaël de Chalendar, Jorge Garcia Flores, Thierry Charnois, Ivan Vladimir Meza Ruiz
In this paper, we take out SERA from the biomedical domain to the general one by adapting its content-based method to successfully evaluate summaries from the general domain.
no code implementations • SEMEVAL 2017 • Ignacio Arroyo-Fern{\'a}ndez, Ivan Vladimir Meza Ruiz
In this paper we report our attempt to use, on the one hand, state-of-the-art neural approaches that are proposed to measure Semantic Textual Similarity (STS).
no code implementations • SEMEVAL 2016 • Oscar William Lightgow Serrano, Ivan Vladimir Meza Ruiz, Albert Manuel Orozco Camacho, Jorge Garcia Flores, Davide Buscaldi