# MyMentorLLM: A psychotherapy GenAI environment with multimodal voice/text patients, trainees and experts for deliberate practice

arXiv: https://arxiv.org/abs/2607.25667 · HTML: https://mlsanity.com/paper/2607.25667/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 52 references that are in the map.
- First posted on arXiv 28 Jul 2026.

## Builds on (most cited first, 13 of 13)

- [Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting](https://mlsanity.com/paper/2305.04388/) (2023)
- [Large Language Model based Multi-Agents: A Survey of Progress and Challenges](https://mlsanity.com/paper/2402.01680/) (2024)
- [Out of One, Many: Using Language Models to Simulate Human Samples](https://mlsanity.com/paper/2209.06899/) (2022)
- [The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions](https://mlsanity.com/paper/2404.13208/) (2024)
- [Crowdsourcing a Word-Emotion Association Lexicon](https://mlsanity.com/paper/1308.6297/) (2013)
- [Quantifying the Persona Effect in LLM Simulations](https://mlsanity.com/paper/2402.10811/) (2024)
- [Large language models that replace human participants can harmfully misportray and flatten identity groups](https://mlsanity.com/paper/2402.01908/) (2024)
- [Speaker and Time-aware Joint Contextual Learning for Dialogue-act Classification in Counselling Conversations](https://mlsanity.com/paper/2111.06647/) (2021)
- [OmniVoice: Towards Omnilingual Zero-Shot Text-to-Speech with Diffusion Language Models](https://mlsanity.com/paper/2604.00688/) (2026)
- [DASentimental: Detecting depression, anxiety and stress in texts via emotional recall, cognitive networks and machine learning](https://mlsanity.com/paper/2110.13710/) (2021)
- [Decomposing Factual Sycophancy in Language Models: How Size and Instruction Tuning Shape Robustness](https://mlsanity.com/paper/2606.06306/) (2026)
- [LLMs can persuade only psychologically susceptible humans on societal issues, via trust in AI and emotional appeals, amid logical fallacies](https://mlsanity.com/paper/2604.16935/) (2026)
- [Mapping how LLMs debate societal issues when shadowing human personality traits, sociodemographics and social media behavior](https://mlsanity.com/paper/2604.27624/) (2026)

## Abstract (arXiv)

Psychotherapists need repeated training and supervision; however, scalability is problematic. We present MyMentorLLM, a multimodal voice- and text-based deliberate-practice environment with 2,100 complete Cognitive Behavioural Therapy (CBT) sessions. Each session links a DSM-5-TR-grounded LLM patient (with major depressive, generalised anxiety or borderline personality disorder), an LLM therapist-in-training and an LLM expert supervisor (powered by Gemma-4, Gemini-3.1-Flash-Live and Qwen-3.6). Sessions were analysed for emotional dynamics, therapeutic competence and diagnostic accuracy against human psychotherapy data. Simulated patients expressed disorder-congruent emotional profiles, which therapists mirrored as in human counselling. LLM trainee competence was rated above human levels in most conditions, while native speech-to-speech was closest to human scores. Supervisor feedback improved diagnostic accuracy in 5 of 7 LLM conditions, whereas symptom identification accuracy increased with model size. This work shows deliberate practice can be simulated for CBT training, although patient fidelity, supervisor calibration and harmful feedback require evaluation via a complex systems perspective.