Dongik Shin

Mitigating Spurious Correlations in Mental Health Analysis: A Contrastive Learning Approach for Cross-Domain Robustness

To address the susceptibility of pre-trained language models (PLMs) to spurious correlations in mental health analysis, we propose a robust framework designed to disentangle genuine clinical signals from superficial artifacts. Our approach integrates a contrastive learning method by using masked language modeling (MLM)...