Ricardo Muñoz Sánchez — accepted AI-conference papers

2024

Pseudonymization Categories across Domain Boundaries

Maria Irena Szawerna, Simon Dobnik, Therese Lindström Tiedemann, Ricardo Muñoz Sánchez, Xuan-Son Vu, Elena Volodina

COLING 2024main

Linguistic data, a component critical not only for research in a variety of fields but also for the development of various Natural Language Processing (NLP) applications, can contain personal information. As a result, its accessibility is limited, both from a legal and an ethical standpoint. One of…

Cited by 3 Source ↗PDF ↗Scholar ↗

2021

Intrinsic Bias Metrics Do Not Correlate with Application Bias

Seraphina Goldfarb-Tarrant, Rebecca Marchant, Ricardo Muñoz Sánchez, Mugdha Pandya, Adam Lopez

ACL 2021long

Natural Language Processing (NLP) systems learn harmful societal biases that cause them to amplify inequality as they are deployed in more and more situations. To guide efforts at debiasing these systems, the NLP community relies on a variety of metrics that quantify bias in models. Some of these me…

Cited by 188 Source ↗PDF ↗Scholar ↗