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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 2 of 2 1 Fairlex: A multilingual benchmark for evaluating fairness in legal text processing ... Chalkidis, Ilias; Passini, Tommaso; Zhang, Sheng. - : Zenodo, 2022 BASE Show details 2 Fairlex: A multilingual benchmark for evaluating fairness in legal text processing ... Chalkidis, Ilias; Passini, Tommaso; Zhang, Sheng; Tomada, Letizia; Schwemer, Sebastian Felix; Søgaard, Anders. - : Zenodo, 2022 Abstract: We present a benchmark suite of four datasets for evaluating the fairness of pre-trained legal language models and the techniques used to fine-tune them for downstream tasks. Our benchmarks cover four jurisdictions (European Council, USA, Swiss, and Chinese), five languages (English, German, French, Italian, and Chinese), and fairness across five attributes (gender, age, nationality/region, language, and legal area). In our experiments, we evaluate pre-trained language models using several group-robust fine-tuning techniques and show that performance group disparities are vibrant in many cases, while none of these techniques guarantee fairness, nor consistently mitigate group disparities. Furthermore, we provide a quantitative and qualitative analysis of our results, highlighting open challenges in the development of robustness methods in legal NLP. ... Keyword: fairlex; fairness; legal URL: https://dx.doi.org/10.5281/zenodo.6322642 https://zenodo.org/record/6322642 BASE Hide details

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