VehicleMemBench: An Executable Benchmark for Multi-User Long-Term Memory in In-Vehicle Agents
With the growing demand for intelligent in-vehicle experiences, vehicle-based agents are evolving from simple assistants to long-term companions. This evolution requires agents to continuously model multi-user preferences and make reliable decisions in the face of inter-user preference conflicts and changing habits over time. However, existing benchmarks are largely limited to single-user, static question-answer settings, failing to capture the temporal evolution of preferences and the multi-user, tool-interactive nature of real vehicle environments. To address this gap, we introduce VehicleMemBench, a multi-user long-context memory benchmark built on an executable in-vehicle simulation e...
| Authors | Yuhao Chen, Yi Xu, Xinyun Ding et al. |
|---|---|
| Primary category | cs.AI |
| Published | 25 March 2026 |
| Last updated at source | 25 March 2026 |
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