<?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>Model-Fingerprinting on wellzhi</title><link>https://wellzhi.github.io/tags/model-fingerprinting/</link><description>Recent content in Model-Fingerprinting on wellzhi</description><generator>Hugo</generator><language>zh-cn</language><lastBuildDate>Wed, 19 Aug 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://wellzhi.github.io/tags/model-fingerprinting/index.xml" rel="self" type="application/rss+xml"/><item><title>深度学习模型版权保护技术分类图谱</title><link>https://wellzhi.github.io/posts/read/2026-08-19_deep-learning-model-copyright-protection-taxonomy/</link><pubDate>Wed, 19 Aug 2026 00:00:00 +0000</pubDate><guid>https://wellzhi.github.io/posts/read/2026-08-19_deep-learning-model-copyright-protection-taxonomy/</guid><description>以七组分类图系统梳理深度学习模型版权保护的问题定义、所有权验证、主动防护、验证场景、威胁模型、评估指标与研究前沿。</description></item><item><title>快速入门 LLM 模型版权安全：从领域全貌到前沿论文</title><link>https://wellzhi.github.io/posts/read/2026-08-17_llm-model-copyright-security/</link><pubDate>Mon, 17 Aug 2026 00:00:00 +0000</pubDate><guid>https://wellzhi.github.io/posts/read/2026-08-17_llm-model-copyright-security/</guid><description>从领域地图、所有权验证、模型指纹与水印，到版权攻击、模型血缘和可信来源验证的一条 LLM 模型版权安全入门路线。</description></item></channel></rss>