XferAgent: Cross-Agent Experience Transfer for Self-Improving LLM Agents
Large language model (LLM) agents can reuse experience from prior task executions to improve performance on subsequent tasks. Although existing methods enable cross-agent experience sharing, differences in agents' execution histories and task requirements make shared experiences difficult to reuse effectively. We propose XferAgent, a framework for cross-agent experience transfer that organizes reusable experience in local and shared experience graphs. XferAgent reconciles compatible contributions from heterogeneous agents while avoiding unreliable merges. For each new task, it selects shared experiences and integrates them with the target agent's local experience to support task execution...
| Authors | Weihao Li, Jun Bai, Shijie Chen et al. |
|---|---|
| Primary category | cs.MA |
| Published | 14 October 2026 |
| Last updated at source | 14 October 2026 |
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