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Move by Move: Measuring and Steering How LLMs Conduct Psychotherapy

A tool-exposed ontology steered models closer to human therapy patterns without fine-tuning, showing how explicit action vocabularies can improve agent behavior.

arXiv
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Source Summary

The researchers define **10 therapeutic moves**, validated with **5 licensed psychologists**. Frontier models used inquiry at up to **3× the human rate**, while exposing the moves as tools improved turn-level alignment by **7–9 percentage points**.

Practical Implication

For builders, this suggests representing desired behavior as explicit, callable actions rather than relying only on prose instructions. A compact action ontology can make agent behavior measurable and steerable without fine-tuning.

Agent-Ready Context
The researchers define **10 therapeutic moves**, validated with **5 licensed psychologists**. Frontier models used inquiry at up to **3× the human rate**, while exposing the moves as tools improved turn-level alignment by **7–9 percentage points**.

For builders, this suggests representing desired behavior as explicit, callable actions rather than relying only on prose instructions. A compact action ontology can make agent behavior measurable and steerable without fine-tuning.

The evidence concerns psychotherapy, where behavioral alignment is safety-sensitive and human distributions are not automatically ideal outcomes. The material does not establish whether the method transfers to coding agents.
Context Map
agentresearch#tool-use#agent-evals#agent-reliability
Uncertainty
The evidence concerns psychotherapy, where behavioral alignment is safety-sensitive and human distributions are not automatically ideal outcomes. The material does not establish whether the method transfers to coding agents.