| Underneath the Numbers: Quantitative and Qualitative Gender Fairness in LLMs for Depression Prediction | Jun 12, 2024 | Depression DetectionFairness | —Unverified | 0 |
| ComFeAT: Combination of Neural and Spectral Features for Improved Depression Detection | Jun 10, 2024 | Depression Detection | —Unverified | 0 |
| Multi-Explainable TemporalNet: An Interpretable Multimodal Approach using Temporal Convolutional Network for User-level Depression Detection | Apr 22, 2024 | Depression Detection | —Unverified | 0 |
| Multi Class Depression Detection Through Tweets using Artificial Intelligence | Apr 19, 2024 | Depression Detection | CodeCode Available | 0 |
| Test-Time Training for Depression Detection | Apr 7, 2024 | Depression Detection | —Unverified | 0 |
| Assessing ML Classification Algorithms and NLP Techniques for Depression Detection: An Experimental Case Study | Apr 3, 2024 | Depression Detectionfeature selection | —Unverified | 0 |
| Diverse Perspectives, Divergent Models: Cross-Cultural Evaluation of Depression Detection on Twitter | Apr 1, 2024 | Depression Detection | —Unverified | 0 |
| MOGAM: A Multimodal Object-oriented Graph Attention Model for Depression Detection | Mar 21, 2024 | Depression DetectionGraph Attention | —Unverified | 0 |
| Depression Detection on Social Media with Large Language Models | Mar 16, 2024 | BenchmarkingDepression Detection | —Unverified | 0 |
| Enhancing Depression-Diagnosis-Oriented Chat with Psychological State Tracking | Mar 12, 2024 | Depression DetectionLanguage Modeling | —Unverified | 0 |
