PatientHub: A Unified Framework for Patient Simulation
Quick summary
arXiv:2602.11684v2 Announce Type: replace-cross Abstract: As Large Language Models increasingly power role-playing applications, simulating patients has become a valuable tool for training counselors and scaling therapeutic assessment. However, prior work remains fragmented: existing approaches rely on incompatible, non-standardized profiles, prompts, and evaluation metrics, hindering reproducibility, fair comparison, and reuse. We introduce PatientHub, a unified and modular framework that standardizes the creation, simulation, and evaluation of LLM-based patients. Our framework provides 16 pa
Key takeaways
- arXiv:2602.11684v2 Announce Type: replace-cross Abstract: As Large Language Models increasingly power role-playing applications, simulating patients has become a valuable tool for training counselors and scaling therapeutic assessment.
- However, prior work remains fragmented: existing approaches rely on incompatible, non-standardized profiles, prompts, and evaluation metrics, hindering reproducibility, fair comparison, and reuse.
- We introduce PatientHub, a unified and modular framework that standardizes the creation, simulation, and evaluation of LLM-based patients.
Why it matters
“PatientHub: A Unified Framework for Patient Simulation” highlights the need for repeatable measurement rather than a single impressive demonstration. Independent validation across datasets and clearly stated limitations determine whether a result can guide product decisions.
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