This article explains the key points of RRSI: Regularized Recursive Self-Improvement of Agent Harnesses. 2026-09-21 (arXiv) Xia, Peng, Han, Rujun, Wang, Zifeng, Chen, Yanfei, Zhuang, Yufan, Lee, Yoonho, Huang, Chengsong, Yu, Han, CuiZhu, Zhongying, Ming, Yifei, et al. Google Cloud AI Research, UNC-Chapel Hill, Stanford University, Washington University in St....

이번 글에서는 RRSI: Regularized Recursive Self-Improvement of Agent Harnesses 논문의 핵심 포인트만 간단히 정리한다. 2026년 9월 21일(Arxiv) Xia, Peng, Han, Rujun, Wang, Zifeng, Chen, Yanfei, Zhuang, Yufan, Lee, Yoonho, Huang, Chengsong, Yu, Han, CuiZhu, Zhongying, Ming, Yifei, et al. Google Cloud AI Research, UNC-Chapel Hill, Stanford University, Washington University in...

This article explains the key points of An Empirical Study of Harness Design for Coding Agents. 2026-09-17 (arXiv) Fan, Run-Ze, Zhang, Zihao, Ma, Simin, Hu, Yebowen, Wang, Shouju, Song, Kaiqiang, Liu, Fei, Zamani, Hamed, Wang, Xiaoyang. UMass Amherst, Zoom, Emory University, UNC Charlotte Paper Read this article in Korean Summary...

이번 글에서는 An Empirical Study of Harness Design for Coding Agents 논문의 핵심 포인트만 간단히 정리한다. 2026년 9월 17일(Arxiv) Fan, Run-Ze, Zhang, Zihao, Ma, Simin, Hu, Yebowen, Wang, Shouju, Song, Kaiqiang, Liu, Fei, Zamani, Hamed, Wang, Xiaoyang. UMass Amherst, Zoom, Emory University, UNC Charlotte 논문 링크 영문판 보기 요약 코딩...

This article explains the key points of The Router Within: Eliciting Native Skill Routing from a Frozen LLM. 2026-09-14 (arXiv), arXiv preprint Chen, Ruishuo, Wang, Xun, Chen, Yu, Li, Zhuoran, Huang, Longbo. Institute for Interdisciplinary Information Sciences, Tsinghua University Paper Read this article in Korean Summary Selecting a skill, a...