PersonaMem-v3: Toward Omni-Platform Personal Intelligence for Holistic User Understanding, Recommendation, and Agentic Tasks
Personal intelligence is becoming a central frontier for user-facing AI agents. To be helpful in everyday life, agents must understand users across the digital contexts where their preferences, intents, habits, social relationships, and needs unfold over time. Today's systems can personalize within individual apps or tasks, but personal intelligence as a whole remains under-measured: how agents build cross-context user understanding, support steerable recommendation systems, act proactively across platforms, and avoid over-personalization. We introduce PersonaMem-v3, a real-world-grounded benchmark and evaluation harness for omni-platform personal intelligence. PersonaMem-v3 is seeded fro...
| Authors | Bowen Jiang, Yuan Yuan, Zhuoqun Hao et al. |
|---|---|
| Primary category | cs.CY |
| Published | 16 July 2026 |
| Last updated at source | 7 October 2026 |
Popularity, last 2 days
0 now. Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- bowen-upenn/PersonaMem-v2Dataset · cited by
- bowen-upenn/PersonaMem-v3Dataset · cited by
- bowen-upenn/PersonaMem-v1Dataset · cited by
Models and datasets referencing this paper
- bowen-upenn/PersonaMem-v2Dataset
- bowen-upenn/PersonaMem-v1Dataset
- bowen-upenn/PersonaMem-v3Dataset
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.