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Preserving Grammatical Gender when Debiasing Word Embeddings in Spanish

Accepted for publication in Issue No. 75 of the SEPLN journal and for presentation at the XLI International SEPLN Conference, 2025.

In this paper, we propose INLP-Gram, an algorithm designed to mitigate gender bias in Spanish word embeddings while preserving grammatical gender information. It is an adaptation of the Iterative Nullspace Projection (INLP).

Team GPLSI at QClef 2025: Quantum-Inspired Instance Selection and Clustering

Accepted at the Conference and Labs of the Evaluation Forum (CLEF 2025).

This paper presents the participation of the GPLSI team in the Quantum CLEF (QClef) Lab at CLEF 2025, focusing on Task 2 - Instance Selection and Task 3 - Clustering.

GPLSICORTEX at SemEval-2025 Task 10: Leveraging Intentions for Generating Narrative Extractions

This paper will be presented in the 19th International Workshop on Semantic Evaluation, 2025.

This paper describes our approach to address the SemEval-2025 Task 10 subtask 3 for the English language, which is focused on narrative extraction given news articles with a dominant narrative.

Mitigation of gender bias in word embeddings in Spanish

Published: November 08, 2024

When applying gender bias mitigation techniques to Spanish static embeddings, we observe the undesired effect of reducing the grammatical gender information of embeddings. An analysis of the gender bias of Spanish embeddings allows us to study ways of preserving grammatical gender while eliminating gender stereotypes.

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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