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Large Language Models (LLMs) have become valuable assets in mental health, showing promise in both classification tasks and counseling applications.
The PHQ-9: validity of a brief depression severity measure
K. Kroenke, R. L. Spitzer, and J. B. Williams · 2001
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Identity management and mental health discourse in social media
U. Pavalanathan and M. De Choudhury · 2015
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Large-scale analysis of counseling conversations: An application of natural language processing to mental health
T. Althoff, K. Clark, and J. Leskovec · 2016
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Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): a randomized controlled trial
K. K. Fitzpatrick, A. Darcy, and M. Vierhile · 2017
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LCA: Loss change allocation for neural network training
J. Lan, R. Liu, H. Zhou, and J. Yosinski · 2019
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Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
C. Rudin · 2019
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Language models are few-shot learners
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, et al · 2020
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On the state of social media data for mental health research
K. Harrigian, C. Aguirre, and M. Dredze · 2021
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Towards an online empathetic chatbot with emotion causes
Y. Li, K. Li, H. Ning, X. Xia, Y. Guo, C. Wei, J. Cui, and B. Wang · 2021
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Towards facilitating empathic conversations in online mental health support: A reinforcement learning approach
A. Sharma, I. W. Lin, A. S. Miner, D. C. Atkins, and T. Althoff · 2021
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PsychBERT: a mental health language model for social media mental health behavioral analysis
V. Vajre, M. Naylor, U. Kamath, and A. Shehu · 2021
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Training a helpful and harmless assistant with reinforcement learning from human feedback
Y. Bai, A. Jones, K. Ndousse, A. Askell, A. Chen, N. DasSarma, D. Drain, S. Fort, D. Ganguli, T. Henighan, N. Joseph, S. Kadavath, J. Kernion, T. Conerly, S. El-Showk, N. Elhage, Z. Hatfield-Dodds, D. Hernandez, T. Hume, S. Johnston, S. Kravec, L. Lovitt, N. Nanda, C. Olsson, D. Amodei, T. Brown, J. Clark, S. McCandlish, C. Olah, B. Mann, and J. Kaplan · 2022
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Is attention explanation? an introduction to the debate
A. Bibal, R. Cardon, D. Alfter, R. Wilkens, X. Wang, T. François, and P. Watrin · 2022
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EmpHi: Generating empathetic responses with human-like intents
M. Y. Chen, S. Li, and Y. Yang · 2022
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Chatbots and mental health: Insights into the safety of generative AI
J. De Freitas, A. K. Uğuralp, Z. Oğuz-Uğuralp, and S. Puntoni · 2022
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Towards intention understanding in suicidal risk assessment with natural language processing
S. Ji · 2022
Cited alongside, same era.
MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare
S. Ji, T. Zhang, L. Ansari, J. Fu, P. Tiwari, and E. Cambria · 2022
Cited alongside, same era.
Rethinking the role of demonstrations: What makes in-context learning work?
S. Min, X. Lyu, A. Holtzman, M. Artetxe, M. Lewis, H. Hajishirzi, and L. Zettlemoyer · 2022
Cited alongside, same era.
Benchmarking for public health surveillance tasks on social media with a domain-specific pretrained language model
U. Naseem, B. C. Lee, M. Khushi, J. Kim, and A. Dunn · 2022
Cited alongside, same era.
Towards motivational and empathetic response generation in online mental health support
T. Saha, V. Gakhreja, A. S. Das, S. Chakraborty, and S. Saha · 2022
Cited alongside, same era.
Domain-specific continued pretraining of language models for capturing long context in mental health
S. Ji, T. Zhang, K. Yang, S. Ananiadou, E. Cambria, and J. Tiedemann · 2023
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Explainable artificial intelligence for mental health through transparency and interpretability for understandability
D. W. Joyce, A. Kormilitzin, K. A. Smith, and A. Cipriani · 2023
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Psy-LLM: Scaling up global mental health psychological services with AI-based large language models, 2023
T. Lai, Y. Shi, Z. Du, J. Wu, K. Fu, Y. Dou, and Z. Wang · 2023
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Understanding client reactions in online mental health counseling
A. Li, L. Ma, Y. Mei, H. He, S. Zhang, H. Qiu, and Z. Lan · 2023
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Help me heal: A reinforced polite and empathetic mental health and legal counseling dialogue system for crime victims
K. Mishra, P. Priya, and A. Ekbal · 2023
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Chain-of-thought prompting elicits reasoning in large language models
J. Wei, X. Wang, D. Schuurmans, M. Bosma, F. Xia, E. Chi, Q. V. Le, D. Zhou, et al · 2022
Cited alongside, same era.
Natural language processing applied to mental illness detection: A narrative review
T. Zhang, A. Schoene, S. Ji, and S. Ananiadou · 2022
Cited alongside, same era.
Will affective computing emerge from foundation models and general artificial intelligence? a first evaluation of ChatGPT
M. M. Amin, E. Cambria, and B. W. Schuller · 2023
Cited alongside, same era.
MindWatch: A smart cloud-based AI solution for suicide ideation detection leveraging large language models
R. Bhaumik, V. Srivastava, A. Jalali, S. Ghosh, and R. Chandrasekharan · 2023
Cited alongside, same era.
Ethical dilemmas, mental health, artificial intelligence, and LLM-based chatbots
J. Cabrera, M. S. Loyola, I. Magaña, and R. Rojas · 2023
Cited alongside, same era.
Seven pillars for the future of artificial intelligence
E. Cambria, R. Mao, M. Chen, Z. Wang, and S.-B. Ho · 2023
Cited alongside, same era.
Why can GPT learn in-context? language models secretly perform gradient descent as meta-optimizers
D. Dai, Y. Sun, L. Dong, Y. Hao, S. Ma, Z. Sui, and F. Wei · 2023
Cited alongside, same era.
Auditing large language models: a three-layered approach
J. Mökander, J. Schuett, H. R. Kirk, and L. Floridi · 2023
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A review of the explainability and safety of conversational agents for mental health to identify avenues for improvement
S. Sarkar, M. Gaur, L. K. Chen, M. Garg, and B. Srivastava · 2023
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Large language models can be easily distracted by irrelevant context
F. Shi, X. Chen, K. Misra, N. Scales, D. Dohan, E. H. Chi, N. Schärli, and D. Zhou · 2023
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M. Turpin, J. Michael, E. Perez, and S. R. Bowman · 2023
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Transformers learn in-context by gradient descent
J. Von Oswald, E. Niklasson, E. Randazzo, J. Sacramento, A. Mordvintsev, A. Zhmoginov, and M. Vladymyrov · 2023
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Interactive natural language processing
Z. Wang, G. Zhang, K. Yang, N. Shi, W. Zhou, S. Hao, G. Xiong, Y. Li, M. Y. Sim, X. Chen, Q. Zhu, Z. Yang, A. Nik, Q. Liu, C. Lin, S. Wang, R. Liu, W. Chen, K. Xu, D. Liu, Y. Guo, and J. Fu · 2023
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A meta-learning perspective on transformers for causal language modeling
X. Wu and L. R. Varshney · 2023
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Mental-LLM: Leveraging large language models for mental health prediction via online text data
X. Xu, B. Yao, Y. Dong, S. Gabriel, H. Yu, J. Hendler, M. Ghassemi, A. K. Dey, and D. Wang · 2023
Closest in time.
Explainability for large language models: A survey
H. Zhao, H. Chen, F. Yang, N. Liu, H. Deng, H. Cai, S. Wang, D. Yin, and M. Du · 2023
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