mlsanityData to 7 Oct 2026

Rethinking Large Language Models in Mental Health Applications

arXiv 2311.11267 ↗First posted 19 Nov 2023cs.CLcited by 16

On the map: LLM reasoning → Clinical and biomedical applications

Abstract (arXiv)

Large Language Models (LLMs) have become valuable assets in mental health, showing promise in both classification tasks and counseling applications. This paper offers a perspective on using LLMs in mental health applications. It discusses the instability of generative models for prediction and the potential for generating hallucinatory outputs, underscoring the need for ongoing audits and evaluations to maintain their reliability and dependability. The paper also distinguishes between the often interchangeable terms ``explainability'' and ``interpretability'', advocating for developing inherently interpretable methods instead of relying on potentially hallucinated self-explanations generated by LLMs. Despite the advancements in LLMs, human counselors' empathetic understanding, nuanced interpretation, and contextual awareness remain irreplaceable in the sensitive and complex realm of mental health counseling. The use of LLMs should be approached with a judicious and considerate mindset, viewing them as tools that complement human expertise rather than seeking to replace it.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Placed in Clinical and biomedical applications, one of 17 directions in LLM reasoning. Builds on 27 of its 49 references that are in the map. First posted on arXiv 19 Nov 2023.

Builds on

27 of 49 references.

References · 27

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  3. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,634
  4. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,383
  5. 2022Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?cited by 1,413
  6. 2023Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Promptingcited by 1,081
  7. 2023Large Language Models Can Be Easily Distracted by Irrelevant Contextcited by 820
  8. 2022Transformers learn in-context by gradient descentcited by 714
  9. 2023Explainability for Large Language Models: A Surveycited by 331
  10. 2021MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcarecited by 159
  11. 2023Auditing large language models: a three-layered approachcited by 135
  12. 2021Towards Facilitating Empathic Conversations in Online Mental Health Support: A Reinforcement Learning Approachcited by 75
15 more
  1. 2023Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Datacited by 66
  2. 2023Towards Interpretable Mental Health Analysis with Large Language Modelscited by 53
  3. 2023SMILE: Single-turn to Multi-turn Inclusive Language Expansion via ChatGPT for Mental Health Supportcited by 46
  4. 2023ChatCounselor: A Large Language Models for Mental Health Supportcited by 44
  5. 2020On the State of Social Media Data for Mental Health Researchcited by 32
  6. 2023Interactive Natural Language Processingcited by 31
  7. 2023Domain-specific Continued Pretraining of Language Models for Capturing Long Context in Mental Healthcited by 25
  8. 2023Enhancing Psychological Counseling with Large Language Model: A Multifaceted Decision-Support System for Non-Professionalscited by 24
  9. 2021Towards an Online Empathetic Chatbot with Emotion Causescited by 16
  10. 2023A Benchmark for Understanding Dialogue Safety in Mental Health Supportcited by 13
  11. 2019LCA: Loss Change Allocation for Neural Network Trainingcited by 9
  12. 2022EmpHi: Generating Empathetic Responses with Human-like Intentscited by 9
  13. 2023Understanding Client Reactions in Online Mental Health Counselingcited by 9
  14. 2022Benchmarking for Public Health Surveillance tasks on Social Media with a Domain-Specific Pretrained Language Modelcited by 7
  15. 2023A Meta-Learning Perspective on Transformers for Causal Language Modelingcited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 7; 2025: 5; 2026: 4.

16 papers.

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  1. 2024Can Large Language Models be Good Emotional Supporter? Mitigating Preference Bias on Emotional Support Conversationcited by 55
  2. 2024Large Language Models in Mental Health Care: a Scoping Reviewcited by 34
  3. 2024Understanding the Therapeutic Relationship between Counselors and Clients in Online Text-based Counseling using LLMscited by 19
  4. 2025When Can We Trust LLMs in Mental Health? Large-Scale Benchmarks for Reliable LLM Evaluationcited by 19
  5. 2025Can Large Language Models Identify Implicit Suicidal Ideation? An Empirical Evaluationcited by 13
  6. 2024CBT-Bench: Evaluating Large Language Models on Assisting Cognitive Behavior Therapycited by 12
  7. 2025Can You Share Your Story? Modeling Clients' Metacognition and Openness for LLM Therapist Evaluationcited by 7
  8. 2024Harnessing Large Language Models Over Transformer Models for Detecting Bengali Depressive Social Media Text: A Comprehensive Studycited by 6
  9. 2024Zero-shot Explainable Mental Health Analysis on Social Media by Incorporating Mental Scalescited by 6
  10. 2025Toward Clinically Explainable AI for Medical Diagnosis: A Foundation Model with Human-Compatible Reasoning via Reinforcement Learningcited by 5
  11. 2024Automating PTSD Diagnostics in Clinical Interviews: Leveraging Large Language Models for Trauma Assessmentscited by 4
  12. 2025Can LLMs Address Mental Health Questions? A Comparison with Human Therapistscited by 4
4 more
  1. 2026Keyphrase Generative Representation of Youth Crisis Conversations Beyond Static Taxonomiescited by 1
  2. 2026CARE: An Explainable Computational Framework for Assessing Client-Perceived Therapeutic Alliance Using Large Language Modelscited by 0
  3. 2026Training Therapeutic Judges and Multi-Agent Systems for Human-Aligned Mental Health Supportcited by 0
  4. 2026BiGraph-Diffuse: A Bidirectional Diffusion Language Model with Graph-Structured Retrieval For Mental Health Counselingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Do Large Language Models Align with Core Mental Health Counseling Competencies?
  2. 2026A Systematic Evaluation of Large Language Models for PTSD Severity Estimation: The Role of Contextual Knowledge and Modeling Strategies
  3. 2025Independent Clinical Evaluation of General-Purpose LLM Responses to Signals of Suicide Risk
  4. 2026Analyzing LLM Reasoning to Uncover Mental Health Stigma
  5. 2025Beyond Empathy: Integrating Diagnostic and Therapeutic Reasoning with Large Language Models for Mental Health Counseling
  6. 2025PsychBench: A comprehensive and professional benchmark for evaluating the performance of LLM-assisted psychiatric clinical practice
  7. 2026Retrieval-Augmented Generation in LLMs for Mental Health: Quantifying the Incremental Contribution of Retrieval Within a Layered Safety Architecture
  8. 2023Understanding the Benefits and Challenges of Using Large Language Model-based Conversational Agents for Mental Well-being Support