{"blog_url":"https://www.sbintuitions.co.jp/blog/","url":"https://www.sbintuitions.co.jp/blog/entry/2025/06/20/143234","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fwww.sbintuitions.co.jp%2Fblog%2Fentry%2F2025%2F06%2F20%2F143234\" title=\"ICML 2025\u306b\u8ad6\u6587\u304c\u63a1\u629e\u3055\u308c\u307e\u3057\u305f - SB Intuitions TECH BLOG\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","width":"100%","categories":["Publications"],"description":"\u6a5f\u68b0\u5b66\u7fd2\u306e\u30c8\u30c3\u30d7\u30ab\u30f3\u30d5\u30a1\u30ec\u30f3\u30b9\u3067\u3042\u308b International Conference on Machine Learning (ICML) 2025\u306b\u304a\u3044\u3066\u3001\u4ee5\u4e0b\u306e\u8ad6\u6587\u304c\u63a1\u629e\u3055\u308c\u307e\u3057\u305f\u3002 Scaling Laws for Upcycling Mixture-of-Experts Language Models Seng Pei Liew, Takuya Kato, Sho Takase \u8ad6\u6587\uff1ahttps://openreview.net/forum?id=ZBBo19jldX \u30b3\u30fc\u30c9\uff1ahttps://github.com/sbintuitions/sparse-upcycling-scali\u2026","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/s/spliew/20250616/20250616161111.png","type":"rich","title":"ICML 2025\u306b\u8ad6\u6587\u304c\u63a1\u629e\u3055\u308c\u307e\u3057\u305f","author_name":"spliew","published":"2025-06-20 14:32:34","height":"190","blog_title":"SB Intuitions TECH BLOG","provider_name":"Hatena Blog","provider_url":"https://hatena.blog","version":"1.0","author_url":"https://blog.hatena.ne.jp/spliew/"}