Decision-aware User Simulation Agent for Evaluating Conversational Recommender Systems
Conversational recommender systems (CRS) increasingly rely on user simulators for automated evaluation of sales agents. A key requirement for such simulators is the ability to model human decision-making. However, most existing simulation frameworks do not explicitly model the internal decision process, and LLM-based simulators often exhibit unrealistically strong information-processing capabilities, rarely exhibit the hesitation or decision deferral commonly observed in real consumer behavior, resulting in overly high acceptance probabilities. To address this limitation, we propose Hesitator, a theory-grounded user simulation framework that explicitly models human decision-making under c...
| Authors | Yuan-Chi Li, Li-Chi Chen, Sung-Yi Wu et al. |
|---|---|
| Primary category | cs.IR |
| Published | 5 May 2026 |
| Last updated at source | 5 May 2026 |
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