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arXiv · 2506.11381

A Variational Approach for Mitigating Entity Bias in Relation Extraction

Samuel Mensah·Elena Kochkina·Jabez Magomere·Joy Prakash Sain·Simerjot Kaur·Charese Smiley
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Abstract

Mitigating entity bias is a critical challenge in Relation Extraction (RE), where models often rely excessively on entities, resulting in poor generalization. This paper presents a novel approach to address this issue by adapting a Variational Information Bottleneck (VIB) framework. Our method compresses entity-specific information while preserving task-relevant features. It achieves state-of-the-art performance on relation extraction datasets across general, financial, and biomedical domains, in both indomain (original test sets) and out-of-domain (modified test sets with type-constrained entity replacements) settings. Our approach offers a robust, interpretable, and theoretically grounded methodology.

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Samuel Mensah, Elena Kochkina, Jabez Magomere, Joy Prakash Sain, Simerjot Kaur, Charese Smiley. 2025-06-13. A Variational Approach for Mitigating Entity Bias in Relation Extraction. https://arxiv.org/abs/2506.11381

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