TherapyGym: Evaluating and Aligning Clinical Fidelity and Safety in Therapy Chatbots
Jan 1, 2026·,,
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Fangrui Huang
Souhad Chbeir
Arpandeep Khatua
Sheng Wang
Sijun Tan
Kenan Ye
Lillian Annabelle Bailey
Merryn Daniel
Ryan Louie
Sanmi Koyejo
Ehsan Adeli
Abstract
TherapyGym presents a comprehensive framework for evaluating and aligning clinical fidelity and safety in therapy chatbots, addressing critical concerns in mental health AI applications.
Type
Publication
Submitted to International Conference on Machine Learning
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Sheng Wang
(Forence)
PhD Graduate in Computer Science
Sheng Wang is a PhD graduate from The University of Hong Kong, supervised by Prof. Chuan Wu and Prof. Lingpeng Kong.
His research focuses on Agent, LLM Super-Alignment, and Data Synthesis. He has published 14+ papers in top-tier
conferences including NIPS2025 (Spotlight), ICLR2025, ACL2024/2025, EMNLP2025.
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