Measuring the Behavioral Fidelity of Long-Horizon Human Activity Simulations
As LLM-based human simulators are increasingly used for policy, evaluation, and training, they must faithfully reproduce real behavioral patterns. While prior work has examined behavioral fidelity in survey responses and dialogue, longer-horizon real-world activity remains largely unexplored. We introduce a framework for evaluating behavioral fidelity in long-horizon activity simulations across temporal granularities and levels of analysis. As a case study, we collect a 43-hour multi-camera dataset of in-the-wild office activity and compare trace-derived conditioning mechanisms: persona descriptors, few-shot exemplars, and statistical transition and time-of-day priors. We find that behavi...
| Authors | Yi Fei Cheng, Fan Yang, Iremsu Bas et al. |
|---|---|
| Primary category | cs.AI |
| Published | 1 September 2026 |
| Last updated at source | 1 September 2026 |
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