1 code implementation • 27 Mar 2023 • Alex Jones, Isaac Caswell, Ishank Saxena, Orhan Firat
Neural machine translation (NMT) has progressed rapidly over the past several years, and modern models are able to achieve relatively high quality using only monolingual text data, an approach dubbed Unsupervised Machine Translation (UNMT).
no code implementations • 5 Jun 2022 • Alex Jones
We compile a corpus of over 93, 000 Kalaallisut sentences and over 140, 000 Danish sentences, then use cross-lingual sentence embeddings and approximate nearest-neighbors search in an attempt to mine near-translations from these corpora.
1 code implementation • 29 Apr 2022 • Xinyi Zhang, Cong Hao, Peipei Zhou, Alex Jones, Jingtong Hu
The heterogeneity in ML models comes from multi-sensor perceiving and multi-task learning, i. e., multi-modality multi-task (MMMT), resulting in diverse deep neural network (DNN) layers and computation patterns.
1 code implementation • EMNLP 2021 • Alex Jones, William Yang Wang, Kyle Mahowald
We verify some of our linguistic findings by looking at the effect of morphological segmentation on English-Inuktitut alignment, in addition to examining the effect of word order agreement on isomorphism for 66 zero-shot language pairs from a different corpus.
1 code implementation • 10 Apr 2021 • Alex Jones, Derry Tanti Wijaya
The explosion of user-generated content (UGC)--e. g. social media posts, comments, and reviews--has motivated the development of NLP applications tailored to these types of informal texts.
1 code implementation • RANLP (BUCC) 2021 • Alex Jones, Derry Tanti Wijaya
Obtaining high-quality parallel corpora is of paramount importance for training NMT systems.
1 code implementation • 5 Apr 2020 • Wei Ye, Omid Askarisichani, Alex Jones, Ambuj Singh
The learned deep representation for a graph is a dense and low-dimensional vector that captures complex high-order interactions in a vertex neighborhood.