LifeMem: Enabling Lifelong Experience Reuse for LLM Agents
Large language model agents are expected to continuously adapt to new tasks and environments over their lifetime by reusing past experience. However, existing memory-based agents struggle to transfer reusable experience across environments and suffer from catastrophic forgetting as experience accumulated. To address these challenges, we propose LifeMem, a lifelong learning framework that enables agents to transfer knowledge across multiple environments. During learning, LifeMem clusters accumulated interaction trajectories based on underlying workflows to extract reusable skills. When solving a new task at inference time, the agent recalls relevant skills and trajectories to guide actions...
| Authors | Yuli Qiu, Yutong Li, Wei Su et al. |
|---|---|
| Primary category | cs.CL |
| Published | 11 September 2026 |
| Last updated at source | 11 September 2026 |
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