Unveiling and Mitigating Bias in Mental Health Analysis with Large Language Models

Roberta: A robustly optimized bert pretraining approach

Original

Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907

Earlier work this paper cites.

Predicting depression via social media

Munmun De Choudhury, Michael Gamon, Scott Counts, and Eric Horvitz. 2013 · 2013

Earlier work this paper cites.

Scaling-up treatment of depression and anxiety: a global return on investment analysis

Dan Chisholm, Kim Sweeny, Peter Sheehan, Bruce Rasmussen, Filip Smit, Pim Cuijpers, and Shekhar Saxena. 2016 · 2016

Earlier work this paper cites.

Equality of opportunity in supervised learning

Moritz Hardt, Eric Price, and Nati Srebro. 2016 · 2016

Earlier work this paper cites.

Knowledge-aware assessment of severity of suicide risk for early intervention

Manas Gaur, Amanuel Alambo, Joy Prakash Sain, Ugur Kursuncu, Krishnaprasad Thirunarayan, Ramakanth Kavuluru, Amit Sheth, Randy Welton, and Jyotishman Pathak. 2019 · 2019

Earlier work this paper cites.

Bert: Pre-training of deep bidirectional transformers for language understanding

Jacob Devlin Ming-Wei Chang Kenton and Lee Kristina Toutanova. 2019 · 2019

Earlier work this paper cites.

Detection of suicide ideation in social media forums using deep learning

Michael Mesfin Tadesse, Hongfei Lin, Bo Xu, and Liang Yang. 2019 · 2019

Earlier work this paper cites.

Dreaddit: A reddit dataset for stress analysis in social media

Elsbeth Turcan and Kathleen Mckeown. 2019 · 2019

Earlier work this paper cites.

Detection of mental health from reddit via deep contextualized representations

Zheng Ping Jiang, Sarah Ita Levitan, Jonathan Zomick, and Julia Hirschberg. 2020 · 2020

Earlier work this paper cites.

Sensemood: depression detection on social media

Chenhao Lin, Pengwei Hu, Hui Su, Shaochun Li, Jing Mei, Jie Zhou, and Henry Leung. 2020 · 2020

Earlier work this paper cites.

Artificial intelligence in mental health and the biases of language based models

Isabel Straw and Chris Callison-Burch. 2020 · 2020

Earlier work this paper cites.

Sad: A stress annotated dataset for recognizing everyday stressors in sms-like conversational systems

Matthew Louis Mauriello, Thierry Lincoln, Grace Hon, Dorien Simon, Dan Jurafsky, and Pablo Paredes. 2021 · 2021

Earlier work this paper cites.

Audibert: A deep transfer learning multimodal classification framework for depression screening

Ermal Toto, ML Tlachac, and Elke A Rundensteiner. 2021 · 2021

Earlier work this paper cites.

Psychbert: a mental health language model for social media mental health behavioral analysis

Vedant Vajre, Mitch Naylor, Uday Kamath, and Amarda Shehu. 2021 · 2021

Earlier work this paper cites.

Empirical quantitative analysis of covid-19 forecasting models

Yun Zhao, Yuqing Wang, Junfeng Liu, Haotian Xia, Zhenni Xu, Qinghang Hong, Zhiyang Zhou, and Linda Petzold. 2021b · 2021

Earlier work this paper cites.

Machine learning models to detect anxiety and depression through social media: A scoping review

Arfan Ahmed, Sarah Aziz, Carla T Toro, Mahmood Alzubaidi, Sara Irshaidat, Hashem Abu Serhan, Alaa A Abd-Alrazaq, and Mowafa Househ. 2022 · 2022

Cited alongside, same era.

Cams: An annotated corpus for causal analysis of mental health issues in social media posts

Muskan Garg, Chandni Saxena, Sriparna Saha, Veena Krishnan, Ruchi Joshi, and Vijay Mago. 2022 · 2022

Cited alongside, same era.

Chain-of-thought prompting elicits reasoning in large language models

Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022 · 2022

Cited alongside, same era.

Gpt-4 technical report

Original

Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023

Cited alongside, same era.

Detection and classification of anxiety in university students through the application of machine learning

Deep learning and machine learning in psychiatry: a survey of current progress in depression detection, diagnosis and treatment

Matthew Squires, Xiaohui Tao, Soman Elangovan, Raj Gururajan, Xujuan Zhou, U Rajendra Acharya, and Yuefeng Li. 2023 · 2023

Later among the works it cites.

Gemini: a family of highly capable multimodal models

Original

Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al. 2023 · 2023

Later among the works it cites.

A call to action on assessing and mitigating bias in artificial intelligence applications for mental health

Adela C Timmons, Jacqueline B Duong, Natalia Simo Fiallo, Theodore Lee, Huong Phuc Quynh Vo, Matthew W Ahle, Jonathan S Comer, LaPrincess C Brewer, Stacy L Frazier, and Theodora Chaspari. 2023 · 2023

Later among the works it cites.

Llama 2: Open foundation and fine-tuned chat models

Original

Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023

Later among the works it cites.