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Exploring the Capabilities of a Language Model-Only Approach for Depression Detection in Text Data
16 references·1 citing·41 second hop
Exploring the Capabilities of a Language Model-Only Approach for Depression Detection in Text Data (2023)Exploring the Capabilities of a Language …Automatic Depression Detection: an Emotional Audio-Textual Corpus and A Gru/Bilstm-Based Model (2022)Automatic Depression Detectio…Spectral Representation of Behaviour Primitives for Depression Analysis (2020)Spectral Representation of Be…RoBERTa: A Robustly Optimized BERT Pretraining Approach (2019)RoBERTa: A Robustly Optimized…Multi-level Attention Network using Text, Audio and Video for Depression Prediction (2019)Multi-level Attention Network…AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition (2019)AVEC 2019 Workshop and Challe…Detecting Depression with Audio/Text Sequence Modeling of Interviews (2018)Detecting Depression with Aud…Topic Modeling Based Multi-modal Depression Detection (2017)Topic Modeling Based Multi-mo…Multimodal Measurement of Depression Using Deep Learning Models (2017)Multimodal Measurement of Dep…Multimodal and Multiresolution Depression Detection from Speech and Facial Landmark Features (2016)Multimodal and Multiresolutio…Detecting Depression using Vocal, Facial and Semantic Communication Cues (2016)Detecting Depression using Vo…AVEC 2016 (2016)AVEC 2016The Distress Analysis Interview Corpus of human and computer interviews (2014)The Distress Analysis Intervi…SimSensei kiosk: a virtual human interviewer for healthcare decision support (2014)SimSensei kiosk: a virtual hu…Detecting depression from facial actions and vocal prosody (2009)Detecting depression from fac…The PHQ-8 as a measure of current depression in the general population (2008)The PHQ-8 as a measure of cur…Facial Action Coding System (1978)Facial Action Coding SystemZero-Shot Strike: Testing the generalisation capabilities of out-of-the-box LLM models for depression detection (2024)Zero-Shot Strike: Testing the…The PHQ-9 (2001)The Patient Health Questionnaire Somatic, Anxiety, and Depressive Symptom Scales: a systematic review (2010)Diagnostic and Statistical Manual of Mental Disorders (2013)Diagnostic and Statistical Manual of Mental Disorders (2013)The Oregon Experiment — Effects of Medicaid on Clinical Outcomes (2013)Factors associated with depression, anxiety, and PTSD symptomatology during the COVID-19 pandemic: Clinical implications for U.S. young adult mental health (2020)Language use of depressed and depression-vulnerable college students (2004)It’s only a computer: Virtual humans increase willingness to disclose (2014)Synchrony in Psychotherapy: A Review and an Integrative Framework for the Therapeutic Alliance (2016)Voice Interfaces in Everyday Life (2018)A RATING SCALE FOR DEPRESSION (1960)Diagnostic and Statistical Manual of Mental Disorders (2008)AVEC 2014 (2014)Manual for the State-Trait Anxiety Inventory (1970)The PHQ-9: A New Depression Diagnostic and Severity Measure (2002)Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. 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References

  • 2019RoBERTa: A Robustly Optimized BERT Pretraining Approach16,988 cited
  • 1978Facial Action Coding System6,011 cited
  • 2008The PHQ-8 as a measure of current depression in the general population5,113 cited
  • 2014The Distress Analysis Interview Corpus of human and computer interviews591 cited
  • 2014SimSensei kiosk: a virtual human interviewer for healthcare decision support553 cited
  • 2016AVEC 2016505 cited
  • 2009Detecting depression from facial actions and vocal prosody494 cited
  • 2019AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition407 cited
  • 2018Detecting Depression with Audio/Text Sequence Modeling of Interviews350 cited
  • 2016Detecting Depression using Vocal, Facial and Semantic Communication Cues218 cited
  • 2022Automatic Depression Detection: an Emotional Audio-Textual Corpus and A Gru/Bilstm-Based Model201 cited
  • 2017Multimodal Measurement of Depression Using Deep Learning Models175 cited
  • 2017Topic Modeling Based Multi-modal Depression Detection155 cited
  • 2020Spectral Representation of Behaviour Primitives for Depression Analysis149 cited
  • 2016Multimodal and Multiresolution Depression Detection from Speech and Facial Landmark Features

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146 cited
  • 2019Multi-level Attention Network using Text, Audio and Video for Depression Prediction146 cited
  • Cited by

    • 2024Zero-Shot Strike: Testing the generalisation capabilities of out-of-the-box LLM models for depression detection40 cited