<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>模型压缩 on AI 早报</title><link>https://ai-news.example.com/categories/%E6%A8%A1%E5%9E%8B%E5%8E%8B%E7%BC%A9/</link><description>Recent content in 模型压缩 on AI 早报</description><generator>Hugo</generator><language>zh-CN</language><lastBuildDate>Mon, 06 Jul 2026 03:29:09 +0800</lastBuildDate><atom:link href="https://ai-news.example.com/categories/%E6%A8%A1%E5%9E%8B%E5%8E%8B%E7%BC%A9/feed.xml" rel="self" type="application/rss+xml"/><item><title>[EN] Cappy：轻量评分器超越并增强大型多任务语言模型</title><link>https://ai-news.example.com/articles/en-cappy/</link><pubDate>Mon, 06 Jul 2026 03:29:09 +0800</pubDate><guid>https://ai-news.example.com/articles/en-cappy/</guid><description>Google Research 提出 Cappy，一个基于 RoBERTa 的 3.6 亿参数轻量预训练评分器，能够在不微调大型语言模型的情况下，通过输入指令与候选响应输出正确性评分，极大降低了计算和存储成本。</description></item></channel></rss>