Explainable Calibrated Hierarchical XLM-R for Bilingual PHQ-9 Depression Severity Classification

The study proposes a calibration-aware hierarchical XLM-R framework for five-level PHQ-9-guided depression severity classification in Bangla and English. Its key contributions are hierarchical modeling of three open-ended responses with ordinal-aware learning, bilingual performance analysis, improved confidence reliability through temperature scaling, and interpretable prediction analysis using hierarchical attention and LIME.