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Pretrained language models have been used in various natural language processing applications.
RoBERTa: A robustly optimized bert pretraining approach
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.
Longformer: The long-document transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan. 2020 · 2004
Earlier work this paper cites.
Crowdsourcing a word-emotion association lexicon
Saif M. Mohammad and Peter D. Turney. 2013 · 2013
Earlier work this paper cites.
Vader: A parsimonious rule-based model for sentiment analysis of social media text
Clayton Hutto and Eric Gilbert. 2014 · 2014
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
Clpsych 2015 shared task: Depression and ptsd on twitter
Glen Coppersmith, Mark Dredze, Craig Harman, Kristy Hollingshead, and Margaret Mitchell. 2015 · 2015
Earlier work this paper cites.
A hybrid statistical and semantic model for identification of mental health and behavioral disorders using social network analysis
Madan Krishnamurthy, Khalid Mahmood, and Pawel Marcinek. 2016 · 2016
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Supervised learning for suicidal ideation detection in online user content
Shaoxiong Ji, Celina Ping Yu, Sai-fu Fung, Shirui Pan, and Guodong Long. 2018 · 2018
Earlier work this paper cites.
Identifying depression on reddit: The effect of training data
Inna Pirina and Çağrı Çöltekin. 2018 · 2018
Earlier work this paper cites.
Expert, crowdsourced, and machine assessment of suicide risk via online postings
Han-Chin Shing, Suraj Nair, Ayah Zirikly, Meir Friedenberg, Hal Daumé III, and Philip Resnik. 2018 · 2018
Earlier work this paper cites.
Transformer-XL: Attentive Language Models beyond a Fixed-Length Context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G Carbonell, Quoc Le, and Ruslan Salakhutdinov. 2019 · 2019
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Dreaddit: A Reddit Dataset for Stress Analysis in Social Media
Elsbeth Turcan and Kathleen McKeown. 2019 · 2019
Cited alongside, same era.
XLNet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le. 2019 · 2019
Cited alongside, same era.
Clinical XLNet: Modeling Sequential Clinical Notes and Predicting Prolonged Mechanical Ventilation
Kexin Huang, Abhishek Singh, Sitong Chen, Edward Moseley, Chih-Ying Deng, Naomi George, and Charolotta Lindvall. 2020 · 2020
Cited alongside, same era.
Generation and evaluation of artificial mental health records for natural language processing
Julia Ive, Natalia Viani, Joyce Kam, Lucia Yin, Somain Verma, Stephen Puntis, Rudolf N Cardinal, Angus Roberts, Robert Stewart, and Sumithra Velupillai. 2020 · 2020
Cited alongside, same era.
Natural language processing methods and bipolar disorder: scoping review
Daisy Harvey, Fiona Lobban, Paul Rayson, Aaron Warner, Steven Jones, et al. 2022 · 2022
Later among the works it cites.
Towards intention understanding in suicidal risk assessment with natural language processing
Shaoxiong Ji. 2022 · 2022
Later among the works it cites.
Stress detection using natural language processing and machine learning over social interactions
Tanya Nijhawan, Girija Attigeri, and T Ananthakrishna. 2022 · 2022
Later among the works it cites.
Exploring language markers of mental health in psychiatric stories
Marco Spruit, Stephanie Verkleij, Kees de Schepper, and Floortje Scheepers. 2022 · 2022
Later among the works it cites.
Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, and Denny Zhou. 2022 · 2022
Later among the works it cites.
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Julien Chaumond, Lysandre Debut, Victor Sanh, Clement Delangue, Anthony Moi, Pierric Cistac, Morgan Funtowicz, Joe Davison, Sam Shleifer, et al. 2020 · 2020
Cited alongside, same era.
Suicidal ideation detection: A review of machine learning methods and applications
Shaoxiong Ji, Shirui Pan, Xue Li, Erik Cambria, Guodong Long, and Zi Huang. 2021 · 2021
Cited alongside, same era.
Machine learning and natural language processing in mental health: systematic review
Aziliz Le Glaz, Yannis Haralambous, Deok-Hee Kim-Dufor, Philippe Lenca, Romain Billot, Taylor C Ryan, Jonathan Marsh, Jordan Devylder, Michel Walter, Sofian Berrouiguet, et al. 2021 · 2021
Cited alongside, same era.
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
Cited alongside, same era.
SenticNet 7: A commonsense-based neurosymbolic AI framework for explainable sentiment analysis
Erik Cambria, Qian Liu, Sergio Decherchi, Frank Xing, and Kenneth Kwok. 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.
Suicidal ideation and mental disorder detection with attentive relation networks
Shaoxiong Ji, Xue Li, Zi Huang, and Erik Cambria. 2022a
Cited in the paper.
Natural language processing applied to mental illness detection: A narrative review
Tianlin Zhang, Annika Schoene, Shaoxiong Ji, and Sophia Ananiadou. 2022 · 2022
Later among the works it cites.
Will affective computing emerge from foundation models and General AI? A first evaluation on ChatGPT
Mostafa Amin, Erik Cambria, and Björn Schuller. 2023 · 2023
Closest in time.
Ensemble hybrid learning methods for automated depression detection
Luna Ansari, Shaoxiong Ji, Qian Chen, and Erik Cambria. 2023 · 2023
Closest in time.
The NLP task effectiveness of long-range transformers
Guanghui Qin, Yukun Feng, and Benjamin Van Durme. 2023 · 2023
Closest in time.
On the evaluations of ChatGPT and emotion-enhanced prompting for mental health analysis
Kailai Yang, Shaoxiong Ji, Tianlin Zhang, Qianqian Xie, and Sophia Ananiadou. 2023 · 2023
Closest in time.
Emotion fusion for mental illness detection from social media: A survey
Tianlin Zhang, Kailai Yang, Shaoxiong Ji, and Sophia Ananiadou. 2023 · 2023
Closest in time.