# Working Alliance Transformer for Psychotherapy Dialogue Classification

arXiv: https://arxiv.org/abs/2210.15603 · HTML: https://mlsanity.com/paper/2210.15603/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 24 references that are in the map.
- First posted on arXiv 27 Oct 2022.

## Builds on (most cited first, 11 of 11)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Distributed Representations of Sentences and Documents](https://mlsanity.com/paper/1405.4053/) (2014)
- [Deep Annotation of Therapeutic Working Alliance in Psychotherapy](https://mlsanity.com/paper/2204.05522/) (2022)
- [A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry](https://mlsanity.com/paper/1906.11286/) (2019)
- [Neural Topic Modeling of Psychotherapy Sessions](https://mlsanity.com/paper/2204.10189/) (2022)
- [Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL](https://mlsanity.com/paper/2005.04544/) (2020)
- [Predicting human decision making in psychological tasks with recurrent neural networks](https://mlsanity.com/paper/2010.11413/) (2020)
- [Split Q Learning: Reinforcement Learning with Two-Stream Rewards](https://mlsanity.com/paper/1906.12350/) (2019)
- [SupervisorBot: NLP-Annotated Real-Time Recommendations of Psychotherapy Treatment Strategies with Deep Reinforcement Learning](https://mlsanity.com/paper/2208.13077/) (2022)
- [Knowledge Management System with NLP-Assisted Annotations: A Brief Survey and Outlook](https://mlsanity.com/paper/2206.07304/) (2022)

## Built on by (most cited first, 9 of 9)

- [Understanding the Therapeutic Relationship between Counselors and Clients in Online Text-based Counseling using LLMs](https://mlsanity.com/paper/2402.11958/) (2024)
- [Towards Healthy AI: Large Language Models Need Therapists Too](https://mlsanity.com/paper/2304.00416/) (2023)
- [COMPASS: Computational Mapping of Patient-Therapist Alliance Strategies with Language Modeling](https://mlsanity.com/paper/2402.14701/) (2024)
- [Psychotherapy AI Companion with Reinforcement Learning Recommendations and Interpretable Policy Dynamics](https://mlsanity.com/paper/2303.09601/) (2023)
- [Utterance Classification with Logical Neural Network: Explainable AI for Mental Disorder Diagnosis](https://mlsanity.com/paper/2306.03902/) (2023)
- [TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Arts](https://mlsanity.com/paper/2302.10845/) (2023)
- [Conversational Topic Recommendation in Counseling and Psychotherapy with Decision Transformer and Large Language Models](https://mlsanity.com/paper/2405.05060/) (2024)
- [GenAI for Social Work Field Education: Client Simulation with Real-Time Feedback](https://mlsanity.com/paper/2601.18517/) (2026)
- [CARE: An Explainable Computational Framework for Assessing Client-Perceived Therapeutic Alliance Using Large Language Models](https://mlsanity.com/paper/2602.20648/) (2026)

## Abstract (arXiv)

As a predictive measure of the treatment outcome in psychotherapy, the working alliance measures the agreement of the patient and the therapist in terms of their bond, task and goal. Long been a clinical quantity estimated by the patients' and therapists' self-evaluative reports, we believe that the working alliance can be better characterized using natural language processing technique directly in the dialogue transcribed in each therapy session. In this work, we propose the Working Alliance Transformer (WAT), a Transformer-based classification model that has a psychological state encoder which infers the working alliance scores by projecting the embedding of the dialogues turns onto the embedding space of the clinical inventory for working alliance. We evaluate our method in a real-world dataset with over 950 therapy sessions with anxiety, depression, schizophrenia and suicidal patients and demonstrate an empirical advantage of using information about the therapeutic states in this sequence classification task of psychotherapy dialogues.