Google 新研究提出 AIM 研究智能体,维护排序的创意主题图并由审计器核对代码与创意一致、剔除作弊结果,在两组任务上分别比此前最佳的 ScientistOne 高 1.6 和 4.9 分。AIM 每轮在强主题与未验证创意间分配探索,并在代码偏离创意时重新标注,避免学到错误经验。它达到 ScientistOne 最佳分数的速度最快快 3.1 倍,在可行方案多而优解少的任务上收益最大。
New Google paper shows research agents get better results sooner when they keep a ranked map of ideas and check that code matches each idea, so build both in.
Most agents just keep editing code.
When code drifts from the idea it's scored as, the agent learns the wrong lesson.
AIM sorts ideas into ranked themes and splits each round between strong themes and untested ones. An auditor tosses gamed results and relabels ideas to match the code.
It beat the best prior agent, ScientistOne, by 1.6 and 4.9 points on 2 task groups, and matched ScientistOne's best score up to 3.1x sooner.
Expect the biggest gains on tasks with many possible approaches and few good ones.
来源:Rohan Paul · x.com