普林斯顿论文发现,把来自多个开发者的专用智能体组合起来,可胜过任何单一开发者的通用智能体,GAIA 准确率达 70%。在总开发预算相同的条件下,单独得分最多 35% 的专用智能体组合后达到 70%,比通用智能体中位数高 12 分;但在仅用网页搜索的 SealQA 上,组合系统成本更高、表现更差。作者建议让智能体填补共享系统中的空白,单独得分 19% 的智能体可将组合系统从 40% 提升到 53%。
New Princeton paper finds that combining specialized agents from many developers can beat any single developer's general agent, with GAIA accuracy reaching 70%.
Today most agentic systems are built and controlled by 1 developer, so each team rebuilds the same basic skills. The authors argue this limits scale.
They simulated populations of developers with LLM agents that build agents under a fixed budget, then compared lone systems with a multi-developer system. The multi-developer system splits each task and routes the parts to different developers' agents.
On GAIA with the same total development budget, specialists that each scored at most 35% alone reached 70% together. That is 12 points above the median general agent, while on web-search-only SealQA the combined system did worse at higher cost.
Build agents to fill gaps in shared systems, since an agent scoring 19% alone lifted a combined system from 40% to 53%.
来源:Rohan Paul · x.com