Table 4.
Depression classification performance on the DAIC-WOZ dataset.
| Model | Model category | Macro-F1 ↑ | AUC ↑ | Sensitivity ↑ |
|---|---|---|---|---|
| BERT Fine-tuned | General-domain transformer | 0.74 | 0.80 | 0.71 |
| RoBERTa Fine-tuned | General-domain transformer | 0.76 | 0.82 | 0.73 |
| MentalRoBERTa (Ji et al., 2022) | Mental-health-adapted transformer | 0.80 | 0.86 | 0.78 |
| Prompt-only LLM | Foundation-model baseline | 0.78 | 0.83 | 0.75 |
| Evidence + Logistic Regression | Evidence-based baseline | 0.79 | 0.84 | 0.76 |
| R-GCRED (Proposed) | Retrieval-grounded calibrated framework | 0.84 | 0.89 | 0.82 |
↑ indicates that higher values represent better performance.