Papers with mental health monitoring
Exciting Mood Changes: A Time-aware Hierarchical Transformer for Change Detection Modelling (2024.findings-acl)
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| Challenge: | Existing work on temporally sensitive tasks focuses on predicting mood changes . however, there is little attention given to the importance of longitudinal language modelling . |
| Approach: | They propose a Hawkes process-inspired transformation layer to model the influence of time on users’ posts, capturing both their immediate and historical dynamics. |
| Outcome: | The proposed model outperforms existing models on two existing datasets and shows clear performance gains. |
Combining Hierachical VAEs with LLMs for clinically meaningful timeline summarisation in social media (2024.findings-acl)
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| Challenge: | Existing studies have shown that social media users' posts can help identify depression, bipolar disorder or self-harm. |
| Approach: | They propose a hybrid abstractive summarisation approach combining hierarchical VAEs with LLMs to produce clinically meaningful summaries from social media timelines. |
| Outcome: | The proposed approach produces clinically meaningful summaries from social media user timelines, suitable for mental health monitoring. |