论文提出可动态重组的智能体团队，优化 GPU kernel 快于 FlashInfer 基线

"Evolving Agent Teams"

AI coding agents would get stuck optimizing solutions that are fundamentally limited, and simply adding more agents with fixed roles doesn't necessarily solve the problem.

So this paper introduces a supervisor that continuously reorganizes its agent team based on what is blocking progress. It can create specialized agents for debugging, profiling, or exploring alternative solutions, while preserving lessons from previous attempts in shared memory.

With an extended token budget, the system develops a GPU kernel that runs 1.2x faster than the production FlashInfer baseline, outperforming it on 36 out of 47 workloads. It also achieves 3.44x speedup over FlashKDA on another kernel optimization task using NVIDIA B200 GPUs.

https://alphaxiv.org/abs/2610.36848