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Comparing Human Role-Players and LLM-Simulated Clients in Online Counselling Training: An Analysis of Counselling Patterns

Paper recorded by Signals 4 on 2026-10-29 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-29 on arXiv · recorded by Signals 4 on 2026-10-30

Category: cs.AI · 人工智能 · first seen 2026-10-30

Abstract

This study investigates the capabilities of Large Language Models to simulate counselling clients in educational role-plays in comparison to human role-players. Initially, we recorded role-playing sessions, where novice counsellors interacted with human peers acting as clients, followed by role-plays between humans and clients simulated by Mistrals Mixtral 8x7b using 4-bit quantization. These inte

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#73 most recent of 920 cs.AI papers we have recorded · ↑ newer: Gym-Anything for Robotics: Scaling physical simulations with digital a · ↓ older: FARMS: A Verifiable Foundation for Automated Computational Science
Cite this page: Comparing Human Role-Players and LLM-Simulated Clients in Online Counselling Training: An Analysis of Counselling Patterns: the #73 most recent of 920 cs.AI papers we have recorded (as of 2026-10-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/comparing-human-role-players-and-llm-simulated-clients-in-online-counselling-tra.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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