新闻
HarnessOpt-Bench: Evaluating LLMs at Harness Optimization
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers introduced HarnessOpt-Bench, a benchmark measuring how well large language models optimize AI agent harnesses, the prompts, tools, and orchestration code surrounding models.
- 为何重要
- Matters for engineers building agentic systems who need to evaluate whether LLMs can automatically improve system configurations under budget constraints.
- 注意
- Results show performance varies substantially across tasks and seed regimes, with no clear winner among frontier models or their native harnesses.
收听本摘要
- agent
- agentic
- llm
- prompt
- eval
The Agent Architect
每周一个模式、一个权衡、一个生产事故案例。为构建智能体系统的人准备的每周简报。
每周一封邮件,一键退订。您的地址仅用于发送简报。