Google 与合作者发表论文研究智能体 harness 能否被蒸馏:移除专用 harness 后,宏任务成功率从 23.3% 升至 44.3%,高于基座模型带 harness 时的 41.7%。
Super interesting paper from Google and colleagues.
It studies where it's possible to distill an agent harness.
With the specialized harness removed, macro task success goes from 23.3% to 44.3%. That is higher than the 41.7% the base model reaches with the harness attached.
Harness-Zero uses the optimized harness only during training.
The optimized harness and the deployment harness have different action spaces, so a harnessing agent guided by the optimized harness corrects the student's responses in the deployment action space before they run. Those corrected runs become the training demonstrations.
Across 28 harness-induced behaviors in knowledge work, tool use and science, 82.3% are recovered on average. For frontier models using the same evolved harness, the agent-as-harness form also beats the code-as-harness form.
It remains to be seen how robust the approach is, but it's very interesting to see potential in harness distillation.
Paper: https://t.co/AiBm1p17Lp
Chat with Paper: https://t.co/Nda4XsZgrh
来源:@omarsar0 · x.com