Ana Farinha


2024

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Cultural Transcreation with LLMs as a new product
Beatriz Silva | Helena Wu | Yan Jingxuan | Vera Cabarrão | Helena Moniz | Sara Guerreiro de Sousa | João Almeida | Malene Sjørslev Søholm | Ana Farinha | Paulo Dimas
Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 2)

We present how at Unbabel we have been using Large Language Models to apply a Cultural Transcreation (CT) product on customer support (CS) emails and how we have been testing the quality and potential of this product. We discuss our preliminary evaluation of the performance of different MT models in the task of translating rephrased content and the quality of the translation outputs. Furthermore, we introduce the live pilot programme and the corresponding relevant findings, showing that transcreated content is not only culturally adequate but it is also of high rephrasing and translation quality.

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The Center for Responsible AI Project
Maria Ana Henriques | Ana Farinha | Nuno André | António Novais | Sara Guerreiro de Sousa | Bruno Prezado Silva | Ana Oliveira | Helena Moniz | Andre Martins | Paulo Dimas
Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 2)

This paper describes the project “NextGenAI: Center for Responsible AI”, a 39-month Mobilizing and Green Agenda for Business Innovation funded by the Portuguese Recovery and Resilience Plan, under the Recovery and Resilience Facility (RRF). The project aims to create a new Center for Responsible AI in Portugal, capable of delivering more than 20 AI products in crucial areas like “Life Sciences”, many of which use generative AI, particularly NLP models such as those for Machine Translation, contributing to translating into legislation the European Law included in the EU AI Act, and creating a critical mass in the development of responsible AI technologies. To accomplish this mission, the Center for Responsible AI is formed by an ecosystem of startups and research institutions driving research in a virtuous way by addressing real market needs and opportunities in Responsible AI.