Cross-Scale Transfer Learning for Depression Severity Prediction: From PHQ-8 to HAMD-17 Across Languages and Clinical Paradigms
Sequential LoRA transfer from English PHQ-8 interviews to Chinese HAMD-17 consultations improves depression-score prediction with Qwen3.
The paper proposes sequential LoRA transfer for depression-severity prediction when labeled clinical interviews are scarce. A Qwen3 model is first fine-tuned on 189 English DAIC-WOZ sessions scored with PHQ-8, then the adapter initializes training on 100 Chinese PDCH consultations scored with HAMD-17. On the target task, Qwen3-0.6B reached MAE 4.96, RMSE 6.59, and macro-F1 0.36, while Qwen3-1.7B reached 4.38, 5.62, and 0.46, outperforming target-only and non-LLM baselines. The authors describe a single-site exploratory evaluation and do not claim screening or diagnostic utility.
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