Sliding Windows Forget: Why Long-Running LLM Apps Need Memory Policy
中文摘要
长时间运行的LLM失败多源于上下文选择不当而非推理错误，应用需要有效的内存策略来管理长期记忆。
English Summary
Long-running LLM failures often stem from incomplete context rather than reasoning errors, necessitating effective memory policies to manage state selection.
原文节选
Most long-running LLM failures are not pure reasoning failures. They are state-selection failures: the next model call gets incomplete… Continue reading on Towards AI »