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

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

URI
https://arbor.bfh.ch/handle/arbor/44721
Version
Published
Date Issued
2024-07-26
Author(s)
Puttick, Alexandre Riemann  
Rankwiler, Leander
Ikae, Catherine  
Kurpicz-Briki, Mascha  
Type
Working Paper
Language
English
Subjects

cs.CL

Abstract
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.
DOI
https://doi.org/10.24451/dspace/11511
Publisher DOI
10.48550/arXiv.2407.18689
Publisher URL
https://arxiv.org/abs/2407.18689
Organization
Institute for Data Applications and Security (IDAS)  
IDAS / Applied Machine Intelligence  
Technik und Informatik  
Publisher
Cornell University
Submitter
Kurpicz-Briki, Mascha
Citation apa
Puttick, A. R., Rankwiler, L., Ikae, C., & Kurpicz-Briki, M. (2024). The BIAS Detection Framework: Bias Detection in Word Embeddings and Language Models for European Languages. Cornell University. https://doi.org/10.24451/dspace/11511
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