<?xml version="1.0" encoding="UTF-8"?><resource xmlns="http://datacite.org/schema/kernel-4"><identifier identifierType="URL">https://inrepscholar.com/projects/957</identifier><creators><creator><creatorName>Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio</creatorName></creator></creators><titles><title>neural-machine-translation-by-jointly-learning-to-align-and-translate-2021-018</title></titles><publisher>UFTAN UNIVERSITY</publisher><publicationYear>2021</publicationYear><resourceType resourceTypeGeneral="Text">Masters Thesis</resourceType><descriptions><description descriptionType="Abstract">This record links to a foundational neural machine translation paper that introduced an attention-based alignment approach. It is useful for testing humanities-adjacent computational linguistics records and external document workflows.</description></descriptions></resource>