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    <abstract>As mental health issues continue to rise globally, there is an increasing demand for accessible and scalable therapeutic solutions. Many individuals currently seek support from Large Language Models (LLMs), even though these models have not been validated for use in counseling services. In this paper, we evaluate LLMs’ ability to emulate professional therapists practicing Cognitive Behavioral Therapy (CBT). Using anonymized, transcribed role-play sessions between licensed therapists and clients, we compare two approaches: (1) a generation-only method and (2) a Retrieval-Augmented Generation (RAG) approach using CBT guidelines. We evaluate both proprietary and open-source models for linguistic quality, semantic coherence, and therapeutic fidelity using standard natural language generation (NLG) metrics, natural language inference (NLI), and automated scoring for skills assessment. Our results indicate that while LLMs can generate CBT-like dialogues, they are limited in their ability to convey empathy and maintain consistency.</abstract>
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%0 Conference Proceedings
%T Assessing the Effectiveness of LLMs in Delivering Cognitive Behavioral Therapy
%A Bedi, Navdeep Singh
%A Bucur, Ana-Maria
%A Kando, Noriko
%A Crestani, Fabio
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F bedi-etal-2026-assessing
%X As mental health issues continue to rise globally, there is an increasing demand for accessible and scalable therapeutic solutions. Many individuals currently seek support from Large Language Models (LLMs), even though these models have not been validated for use in counseling services. In this paper, we evaluate LLMs’ ability to emulate professional therapists practicing Cognitive Behavioral Therapy (CBT). Using anonymized, transcribed role-play sessions between licensed therapists and clients, we compare two approaches: (1) a generation-only method and (2) a Retrieval-Augmented Generation (RAG) approach using CBT guidelines. We evaluate both proprietary and open-source models for linguistic quality, semantic coherence, and therapeutic fidelity using standard natural language generation (NLG) metrics, natural language inference (NLI), and automated scoring for skills assessment. Our results indicate that while LLMs can generate CBT-like dialogues, they are limited in their ability to convey empathy and maintain consistency.
%R 10.63317/5davpvjizv9x
%U https://aclanthology.org/2026.lrec-1.372/
%U https://doi.org/10.63317/5davpvjizv9x
%P 4747-4756

Markdown (Informal)

[Assessing the Effectiveness of LLMs in Delivering Cognitive Behavioral Therapy](https://aclanthology.org/2026.lrec-1.372/) (Bedi et al., LREC 2026)

• Assessing the Effectiveness of LLMs in Delivering Cognitive Behavioral Therapy (Bedi et al., LREC 2026)

ACL

• Navdeep Singh Bedi, Ana-Maria Bucur, Noriko Kando, and Fabio Crestani. 2026. Assessing the Effectiveness of LLMs in Delivering Cognitive Behavioral Therapy. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 4747–4756, Palma de Mallorca, Spain. ELRA Language Resource Association.