ExpGraph: Model-Agnostic Experience Learning with Graph-Structured Memory for LLM Agents 事件

ExpGraph: Model-Agnostic Experience Learning with Graph-Structured Memory for LLM Agents arXiv:2605.30712v1 Announce Type: new Abstract: Large language model (LLM) agents have shown strong capabilities in reasoning, tool use, and multi-step interaction, but they often solve tasks from scratch and fail to reuse successful strategies or failure lessons from prior experience. Fine-tuning on collected experience can improve reuse, but it is inflexible when stronger or more suitable executors emerge