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Xiaoliang Chen

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Conference 2026

Mitigating Spurious Correlations in Text Classification Using Latent Space Geometry

This paper introduces a prototype-guided modeling approach that leverages natural language prompts to represent confounders, transforming abstract biases into interpretable geometric anchors without auxiliary classifiers, a novel framework that mitigates spurious correlations by manipulating latent space geometry.

Jiasen Gao, Xiaoliang Chen, Duoqian Miao et al. · 0 citations

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