Measuring and Mitigating the Distributional Gap Between Real and Simulated User Behaviors
As user simulators are increasingly used for interactive training and evaluation of AI assistants, it is essential that they represent the diverse behaviors of real users. While existing works train user simulators to generate human-like responses, whether they capture the broad and heterogeneous distribution of real user behaviors remains an open question. In this work, we introduce a method to measure the distributional gap between real and simulated user behaviors, validated through a human study and ablations. Given a dataset of real and simulated conversations, our method extracts representations of user behavior from each conversation, quantizes them into discrete distributions via ...
| Authors | Shuhaib Mehri, Philippe Laban, Sumuk Shashidhar et al. |
|---|---|
| Primary category | cs.CL |
| Published | 8 May 2026 |
| Last updated at source | 8 May 2026 |
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