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Research PaperResearchia:202608.24010

Move by Move: Measuring and Steering How LLMs Conduct Psychotherapy

Afonso Baldo

Abstract

Users increasingly turn to large language models for emotional support, yet little is known about how these models actually conduct a psychotherapy interaction. We introduce an ontology of ten therapeutic moves: compact, function-based categories grounded in the MULTI-60 inventory, validated through an annotation campaign with five licensed psychologists, and scaled with a judge-based approach that matches expert agreement. Applying it to real counseling transcripts and model-led sessions, we co...

Submitted: August 24, 2026Subjects: NLP; Computational Linguistics

Description / Details

Users increasingly turn to large language models for emotional support, yet little is known about how these models actually conduct a psychotherapy interaction. We introduce an ontology of ten therapeutic moves: compact, function-based categories grounded in the MULTI-60 inventory, validated through an annotation campaign with five licensed psychologists, and scaled with a judge-based approach that matches expert agreement. Applying it to real counseling transcripts and model-led sessions, we compare the move distributions between human clinicians and a panel of frontier models. Models over-use inquiry at up to three times the human rate, neglect psychoeducation, and are strongly context-anchored: they carry forward strategies initiated by a human clinician but rarely initiate them themselves. Exposing the ontology as a set of tools roughly halves the mean deviation from the human move distribution and improves turn-level alignment with human therapist by 7-9 percentage points, without any fine-tuning.


Source: arXiv:2608.21325v1 - http://arxiv.org/abs/2608.21325v1 PDF: https://arxiv.org/pdf/2608.21325v1 Original Link: http://arxiv.org/abs/2608.21325v1

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Date:
Aug 24, 2026
Topic:
Computational Linguistics
Area:
NLP
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