Papers by Seyedehmoniba Ravan
Probabilistic Depression Detection from Textual Time Series (2026.findings-acl)
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| Challenge: | Existing models for depression severity estimations lack uncertainty estimates and temporal interpretability. |
| Approach: | They propose a Probabilistic framework for Depression Detection from clinical interview utterance sequences that predicts PHQ-8 scores while modeling calibrated uncertainty. |
| Outcome: | The proposed framework achieves competitive performance among text-only systems and produces well-calibrated intervals. |