6 citations · 6 across the 2 of their papers we have counts for
2 papers
cs.CL2025
Exploring Performance Variations in Finetuned Translators of Ultra-Low Resource Languages: Do Linguistic Differences Matter?
Isabel Gonçalves, Paulo Cavalin, Claudio Pinhanez
Finetuning pre-trained language models with small amounts of data is a commonly-used method to create translators for ultra-low resource languages such as endangered Indigenous lan…
cs.CL2024★ 6 cited
Harnessing the Power of Artificial Intelligence to Vitalize Endangered Indigenous Languages: Technologies and Experiences
Claudio Pinhanez, Paulo Cavalin, Luciana Storto +9
Since 2022 we have been exploring application areas and technologies in which Artificial Intelligence (AI) and modern Natural Language Processing (NLP), such as Large Language Mode…