微软在一篇论文中提出面向智能体的上下文引导模型路由方法,在多轮场景下按用户轮次在廉价与昂贵模型之间分配任务,关键是让路由器读取会话历史。在多轮电子表格智能体上做零样本路由测试,相同卸载率下读历史的路由器比只看当前请求的多完成 3.3 个百分点的任务。
Interesting paper from Microsoft on context-guided model routing.
They found a nice trick to achieve cost-aware model routing for agents in a multi-turn setting at the user-turn level.
If you route agent turns between a cheap model and an expensive one, they suggest giving the router the session history.
Microsoft tested zero-shot routing on multi-turn spreadsheet agents.
At the same offloading rate, a router that reads the history passes 3.3 points more tasks than one that sees only the current request.
Prompt caching adds a cost to every switch. Switching from the expensive model to the cheap one recovers its cache cost within two calls. Switching up did not break even in their tests.
The cheap model's cost advantage also shrank from 6.8x to 3.2x on longer sessions.
https://arxiv.org/abs/2610.19292
Chat with Paper: https://academy.dair.ai/papers/whose-turn-is-it-context-guided-model-routing-for-stateful-agents-2610.19292
来源:DAIR.AI · x.com