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In this work, we present the contribution of the BLUE team in the eRisk Lab task on searching for symptoms of depression.
Language models are few-shot learners,
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Center for epidemiologic studies depression scale: Review and revision,
W. W. Eaton, C. Muntaner, C. Smith, A. Tien, M. Ybarra, · 2004
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Depression and self-harm risk assessment in online forums,
A. Yates, A. Cohan, N. Goharian, · 2017
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Utilizing neural networks and linguistic metadata for early detection of depression indications in text sequences,
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Mgl-cnn: a hierarchical posts representations model for identifying depressed individuals in online forums,
G. Rao, Y. Zhang, L. Zhang, Q. Cong, Z. Feng, · 2020
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Using twitter social media for depression detection in the canadian population,
R. Skaik, D. Inkpen, · 2020
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Deep learning architectures and strategies for early detection of self-harm and depression level prediction,
A.-S. Uban, P. Rosso, · 2020
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Towards preemptive detection of depression and anxiety in twitter,
D. Owen, J. Camacho-Collados, L. E. Anke, · 2020
Cited alongside, same era.
Early risk detection of self-harm and depression severity using bert-based transformers: ilab at clef erisk 2020 (2020)
R. Martínez-Castaño, A. Htait, L. Azzopardi, Y. Moshfeghi, · 2020
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Mpnet: Masked and permuted pre-training for language understanding,
K. Song, X. Tan, T. Qin, J. Lu, T.-Y. Liu, · 2020
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Early risk detection of pathological gambling, self-harm and depression using bert,
A.-M. Bucur, A. Cosma, L. P. Dinu, · 2021
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Prevalence and impact of diagnosed and undiagnosed depression in the united states,
A. Handy, R. Mangal, T. S. Stead, R. L. Coffee Jr, L. Ganti, · 2022
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Towards intelligent clinically-informed language analyses of people with bipolar disorder and schizophrenia,
A. Aich, A. Quynh, V. Badal, A. Pinkham, P. Harvey, C. Depp, N. Parde, · 2022
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Gpt-4 technical report,
OpenAI, · 2023
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Chataug: Leveraging chatgpt for text data augmentation,
H. Dai, Z. Liu, W. Liao, X. Huang, Z. Wu, L. Zhao, W. Liu, N. Liu, S. Li, D. Zhu, et al., · 2023
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It’s just a matter of time: Detecting depression with time-enriched multimodal transformers,
A.-M. Bucur, A. Cosma, P. Rosso, L. P. Dinu, · 2023
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Detecting symptoms of depression on reddit,
T. Liu, D. Jain, S. R. Rapole, B. Curtis, J. C. Eichstaedt, L. H. Ungar, S. C. Guntuku, · 2023
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On the evaluations of chatgpt and emotion-enhanced prompting for mental health analysis,
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S. Meyer, D. Elsweiler, B. Ludwig, M. Fernandez-Pichel, D. E. Losada, · 2022
Cited alongside, same era.
Multi-aspect transfer learning for detecting low resource mental disorders on social media,
A. S. Uban, B. Chulvi, P. Rosso, · 2022
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Improving the generalizability of depression detection by leveraging clinical questionnaires,
T. Nguyen, A. Yates, A. Zirikly, B. Desmet, A. Cohan, · 2022
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Personachatgen: Generating personalized dialogues using gpt-3,
Y.-J. Lee, C.-G. Lim, Y. Choi, J.-H. Lm, H.-J. Choi, · 2022
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Self-instruct: Aligning language model with self generated instructions,
Y. Wang, Y. Kordi, S. Mishra, A. Liu, N. A. Smith, D. Khashabi, H. Hajishirzi, · 2022
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Mentalbert: Publicly available pretrained language models for mental healthcare,
S. Ji, T. Zhang, L. Ansari, J. Fu, P. Tiwari, E. Cambria, · 2022
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Symptom identification for interpretable detection of multiple mental disorders on social media,
Z. Zhang, S. Chen, M. Wu, K. Zhu,
Cited in the paper.
K. Yang, S. Ji, T. Zhang, Q. Xie, S. Ananiadou, · 2023
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Will affective computing emerge from foundation models and general ai? a first evaluation on chatgpt,
M. M. Amin, E. Cambria, B. W. Schuller, · 2023
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Zeroshotdataaug: Generating and augmenting training data with chatgpt,
S. Ubani, S. O. Polat, R. Nielsen, · 2023
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Overview of erisk 2023: Early risk prediction on the internet,
J. Parapar, P. Martín-Rodilla, D. E. Losada, F. Crestani, · 2023
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R. Taori, I. Gulrajani, T. Zhang, Y. Dubois, X. Li, C. Guestrin, P. Liang, T. B. Hashimoto, Stanford alpaca: An instruction-following llama model, https://github.com/tatsu-lab/stanford_alpaca , 2023
2023
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Enabling early health care intervention by detecting depression in users of web-based forums using language models: Longitudinal analysis and evaluation,
D. Owen, D. Antypas, A. Hassoulas, A. F. Pardiñas, L. Espinosa-Anke, J. C. Collados, et al., · 2023
Closest in time.