DeltaMem: Towards Agentic Memory Management via Reinforcement Learning
Recent advances in persona-centric memory have revealed the powerful capability of multi-agent systems in managing persona memory, especially in conversational scenarios. However, these complex frameworks often suffer from information loss and are fragile across varying scenarios, resulting in suboptimal performance. In this paper, we propose DeltaMem, an agentic memory management system that formulates persona-centric memory management as an end-to-end task within a single-agent setting. To further improve the performance of our agentic memory manager, we draw inspiration from the evolution of human memory and synthesize a user-assistant dialogue dataset along with corresponding operatio...
| Authors | Qi Zhang, Shen Huang, Chu Liu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 2 April 2026 |
| Last updated at source | 2 April 2026 |
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