DemoEvolve: Overcoming Sparse Feedback in Agentic Harness Evolution with Demonstrations 事件

DemoEvolve: Overcoming Sparse Feedback in Agentic Harness Evolution with Demonstrations arXiv:2605.24539v1 Announce Type: new Abstract: Agent harness evolution improves frozen language-model agents by modifying the executable structures around them. We study this paradigm as a form of sample-efficient fast adaptation: instead of updating model weights, an agent can acquire task-specific competence by changing its external harness, while leaving the base model's general capabilities intact. Prio