用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/hiyenwong/ai_collection --skill knowledge-centric-self-improvement命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
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基于 SOC 职业分类
| name | knowledge-centric-self-improvement |
| description | Skill generated from arXiv paper 2607.19592: Knowledge-Centric Self-Improvement |
| metadata | {"arxiv":{"id":"2607.19592","title":"Knowledge-Centric Self-Improvement","authors":["Xuefei Julie Wang","Lauren Hyoseo Yoon","Chengrui Qu","Amanda Zichang Wang","Atharva Sehgal","Eric Mazumdar","Yisong Yue"],"published":"2026-07-21","categories":["cs.AI","cs.CL","cs.LG","cs.MA"],"url":"https://arxiv.org/abs/2607.19592","utility":1}} |
arXiv: 2607.19592
Published: 2026-07-21
Authors: Xuefei Julie Wang, Lauren Hyoseo Yoon, Chengrui Qu, Amanda Zichang Wang, Atharva Sehgal, Eric Mazumdar, Yisong Yue
Categories: cs.AI, cs.CL, cs.LG, cs.MA
Utility: 1.00
Self-improving AI systems typically treat the agent as the object that improves, by optimizing prompts, workflows, harnesses, or even the agent's own code. This agent-centric view can make improvements expensive to maintain and difficult to transfer, because gains become tied to a particular agent design, task distribution, or adaptation run. We study a complementary paradigm: knowledge-centric self-improvement, in which agents remain generic and disposable while the persistent object is a curat...
This paper presents advancements that could be applied to enhance agent capabilities in the areas of cs.AI, cs.CL, cs.LG, cs.MA.
