<?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>Clip on Jeanphilo Blog</title><link>https://shio-chan-dev.github.io/jeanblog/zh/tags/clip/</link><description>Recent content in Clip on Jeanphilo Blog</description><generator>Hugo -- 0.159.2</generator><language>zh-cn</language><lastBuildDate>Sat, 24 Jan 2026 13:22:02 +0800</lastBuildDate><atom:link href="https://shio-chan-dev.github.io/jeanblog/zh/tags/clip/index.xml" rel="self" type="application/rss+xml"/><item><title>对比学习损失函数系列（4/4）：CLIP 对比学习目标</title><link>https://shio-chan-dev.github.io/jeanblog/zh/ai/contrastive-learning/4-clip-contrastive-learning-objective/</link><pubDate>Sat, 24 Jan 2026 13:22:02 +0800</pubDate><guid>https://shio-chan-dev.github.io/jeanblog/zh/ai/contrastive-learning/4-clip-contrastive-learning-objective/</guid><description>从损失函数视角理解 CLIP 的双向对比学习目标，建立跨模态对齐的核心直觉。</description></item><item><title>CLIP 系列（1/3）：原理与对比学习公式——多模态对齐的核心机制</title><link>https://shio-chan-dev.github.io/jeanblog/zh/ai/clip/1-clip-principles-and-contrastive-learning/</link><pubDate>Sat, 24 Jan 2026 12:46:49 +0800</pubDate><guid>https://shio-chan-dev.github.io/jeanblog/zh/ai/clip/1-clip-principles-and-contrastive-learning/</guid><description>用数学公式拆解 CLIP 的对比学习目标、嵌入空间与训练流程，建立可复用的多模态理解框架。</description></item><item><title>CLIP 系列（2/3）：PyTorch 完整可复现实战——从数据到训练闭环</title><link>https://shio-chan-dev.github.io/jeanblog/zh/ai/clip/2-clip-pytorch-reproducible-implementation/</link><pubDate>Sat, 24 Jan 2026 12:46:49 +0800</pubDate><guid>https://shio-chan-dev.github.io/jeanblog/zh/ai/clip/2-clip-pytorch-reproducible-implementation/</guid><description>用 CIFAR-10 + 文本提示搭建最小 CLIP 训练闭环，提供完整可复现的 PyTorch 实战脚本。</description></item><item><title>CLIP 系列（3/3）：工程化与优化——检索、索引与部署实践</title><link>https://shio-chan-dev.github.io/jeanblog/zh/ai/clip/3-clip-engineering-and-optimization/</link><pubDate>Sat, 24 Jan 2026 12:46:49 +0800</pubDate><guid>https://shio-chan-dev.github.io/jeanblog/zh/ai/clip/3-clip-engineering-and-optimization/</guid><description>围绕 CLIP 的工程落地，总结向量索引、批量推理与性能优化的实践路线。</description></item></channel></rss>