HippoCamp: Benchmarking Contextual Agents on Personal Computers
We present HippoCamp, a new benchmark designed to evaluate agents' capabilities on multimodal file management. Unlike existing agent benchmarks that focus on tasks like web interaction, tool use, or software automation in generic settings, HippoCamp evaluates agents in user-centric environments to model individual user profiles and search massive personal files for context-aware reasoning. Our benchmark instantiates device-scale file systems over real-world profiles spanning diverse modalities, comprising 42.4 GB of data across over 2K real-world files. Building upon the raw files, we construct 581 QA pairs to assess agents' capabilities in search, evidence perception, and multi-step reas...
| Authors | Zhe Yang, Shulin Tian, Kairui Hu et al. |
|---|---|
| Primary category | cs.AI |
| Published | 1 April 2026 |
| Last updated at source | 1 April 2026 |
Models and datasets referencing this paper
- MMMem-org/HippoCampDataset
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