The BIAS Detection Framework: Bias Detection in Word Embeddings and Language Models for European Languages

Autor:	Puttick, Alexandre, Rankwiler, Leander, Ikae, Catherine, Kurpicz-Briki, Mascha
Rok vydání:	2024
Předmět:	Computer Science - Computation and Language
Druh dokumentu:	Working Paper
Popis:	The project BIAS: Mitigating Diversity Biases of AI in the Labor Market is a four-year project funded by the European commission and supported by the Swiss State Secretariat for Education, Research and Innovation (SERI). As part of the project, novel bias detection methods to identify societal bias in language models and word embeddings in European languages are developed, with particular attention to linguistic and geographic particularities. This technical report describes the overall architecture and components of the BIAS Detection Framework. The code described in this technical report is available and will be updated and expanded continuously with upcoming results from the BIAS project. The details about the datasets for the different languages are described in corresponding papers at scientific venues.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2407.18689 Zobrazit plný text záznamu View this record from Arxiv