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AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages., , , , , , , , , and 7 other author(s). ACL (1), page 6279-6299. Association for Computational Linguistics, (2022)AmericasNLI: Machine translation and natural language inference systems for Indigenous languages of the Americas., , , , , , , , , and 8 other author(s). Frontiers Artif. Intell., (2022)AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages., , , , , , , , , and 7 other author(s). CoRR, (2021)Athena: Constructing Dialogues Dynamically with Discourse Constraints., , , , , , , , , and 4 other author(s). CoRR, (2020)Findings of the Second AmericasNLP Competition on Speech-to-Text Translation., , , , , , , , , and 24 other author(s). NeurIPS (Competition and Demos), volume 220 of Proceedings of Machine Learning Research, page 217-232. PMLR, (2021)Curate and Generate: A Corpus and Method for Joint Control of Semantics and Style in Neural NLG., , , and . ACL (1), page 5938-5951. Association for Computational Linguistics, (2019)Meeting the Needs of Low-Resource Languages: The Value of Automatic Alignments via Pretrained Models., , , , , , , and . EACL, page 3894-3908. Association for Computational Linguistics, (2023)Open-domain Dialogue Generation: What We Can Do, Cannot Do, And Should Do Next., , , , and . ConvAI@ACL, page 148-165. Association for Computational Linguistics, (2022)How to Adapt Your Pretrained Multilingual Model to 1600 Languages., and . ACL/IJCNLP (1), page 4555-4567. Association for Computational Linguistics, (2021)Since the Scientific Literature Is Multilingual, Our Models Should Be Too., and . CoRR, (2024)