<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>架构 on MessageDaily</title><link>https://inkeast.github.io/MessageDaily/tags/%E6%9E%B6%E6%9E%84/</link><description>Recent content in 架构 on MessageDaily</description><generator>Hugo</generator><language>zh-cn</language><lastBuildDate>Sat, 12 Sep 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://inkeast.github.io/MessageDaily/tags/%E6%9E%B6%E6%9E%84/index.xml" rel="self" type="application/rss+xml"/><item><title>Looped Flows 精读：把“想得更久”做进架构——循环流的局部训练之路</title><link>https://inkeast.github.io/MessageDaily/posts/2026-09-12-looped-flows-reasoning-paper-reading/</link><pubDate>Sat, 12 Sep 2026 00:00:00 +0000</pubDate><guid>https://inkeast.github.io/MessageDaily/posts/2026-09-12-looped-flows-reasoning-paper-reading/</guid><description>AITHYRA 访问研究者的 looped flows：状态化去噪器每步预测解并更新循环状态、ODE/SDE 步更新流状态，用局部训练目标绕开跨步反传的老大难。六个推理基准整体超先前 looped SOTA，ARC-AGI-1 58.8%、ARC-AGI-2 12.2%——循环模型在抽象推理上首次具备与主流推理范式对话的竞争力。</description></item><item><title>NCP-ArchPreview 精读：当语言模型开始预测“概念”而不是 token</title><link>https://inkeast.github.io/MessageDaily/posts/2026-09-12-ncp-archpreview-latent-space-lm-paper-reading/</link><pubDate>Sat, 12 Sep 2026 00:00:00 +0000</pubDate><guid>https://inkeast.github.io/MessageDaily/posts/2026-09-12-ncp-archpreview-latent-space-lm-paper-reading/</guid><description>上海交大 Intern-NCP 团队发布 8.9B/5.73T tokens 的潜空间语言模型 NCP-ArchPreview：在 next-token prediction 之上引入 Next Concept Prediction 目标，仅用 51.3% 训练 tokens 追平 OLMo-3-7B 最终 loss，GSM8K +5.99 分，17M 参数 VQ 模块即可完成领域适配——迄今最大潜空间 LM 实证。</description></item></channel></rss>