<?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>LLM on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/tags/llm/</link><description>Recent content in LLM on 硅基 AGI · 智能体学习与测评</description><generator>Hugo</generator><language>zh-cn</language><copyright>本站内容采用 CC BY-NC-SA 4.0 国际许可协议授权</copyright><lastBuildDate>Thu, 02 Jul 2026 11:31:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/tags/llm/index.xml" rel="self" type="application/rss+xml"/><item><title>LlamaIndex 2026指南：数据驱动的LLM应用</title><link>https://guijiagi.com/posts/llamaindex-2026-guide/</link><pubDate>Thu, 02 Jul 2026 11:31:00 +0800</pubDate><guid>https://guijiagi.com/posts/llamaindex-2026-guide/</guid><description>2026年LlamaIndex框架使用指南，构建数据驱动的LLM应用</description></item><item><title>Ollama 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+0800</pubDate><guid>https://guijiagi.com/posts/ai-common-sense-problem/</guid><description>为什么拥有万亿参数的LLM仍然缺乏基本常识？</description></item><item><title>具身智能进展：机器人+LLM</title><link>https://guijiagi.com/posts/embodied-ai-progress-2026/</link><pubDate>Thu, 02 Jul 2026 10:36:00 +0800</pubDate><guid>https://guijiagi.com/posts/embodied-ai-progress-2026/</guid><description>2026年具身智能重大进展：大语言模型驱动的智能机器人</description></item><item><title>差分隐私在LLM中的应用：保护训练数据的新范式</title><link>https://guijiagi.com/posts/differential-privacy-llm/</link><pubDate>Thu, 02 Jul 2026 10:26:00 +0800</pubDate><guid>https://guijiagi.com/posts/differential-privacy-llm/</guid><description>深入探讨差分隐私技术在大语言模型训练和推理中的应用方法与最新进展</description></item><item><title>Prompt工程2026：从基础技巧到企业级应用</title><link>https://guijiagi.com/posts/prompt-engineering-2026/</link><pubDate>Tue, 30 Jun 2026 09:10:00 +0800</pubDate><guid>https://guijiagi.com/posts/prompt-engineering-2026/</guid><description>2026年Prompt工程全景指南：从基础技巧到结构化Prompt、多模态Prompt、Agent 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+0800</pubDate><guid>https://guijiagi.com/posts/llm-hallucination-2026-analysis/</guid><description>LLM幻觉问题的深度根因分析与2026年最新缓解策略：从RAG到自验证的完整方案</description></item><item><title>LM Studio 2026：桌面级大模型工具评测</title><link>https://guijiagi.com/posts/lm-studio-2026-review/</link><pubDate>Sun, 28 Jun 2026 11:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/lm-studio-2026-review/</guid><description>深度评测 LM Studio 2026 版本，从模型管理、对话界面、API 服务到 RAG 构建的全面分析</description></item><item><title>Ollama 2026：本地大模型运行的最佳实践</title><link>https://guijiagi.com/posts/ollama-2026-local-llm/</link><pubDate>Sun, 28 Jun 2026 11:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ollama-2026-local-llm/</guid><description>全面介绍 Ollama 2026 版本的特性、模型管理、API 使用、性能优化与生产部署最佳实践</description></item><item><title>vLLM 2026 生产部署完全指南</title><link>https://guijiagi.com/posts/vllm-2026-deployment-guide/</link><pubDate>Sun, 28 Jun 2026 11:00:00 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+0800</pubDate><guid>https://guijiagi.com/posts/prompt-engineering-2026-practices/</guid><description>2026年Prompt工程已从个人技巧发展为系统化工程体系，本文全面梳理从设计、测试、版本管理到监控的完整流程</description></item><item><title>大模型评估流水线搭建：从 Benchmark 到自定义评测</title><link>https://guijiagi.com/posts/llm-evaluation-pipeline-benchmark-to-custom/</link><pubDate>Sun, 28 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-evaluation-pipeline-benchmark-to-custom/</guid><description>系统讲解大模型评估流水线的搭建方法，涵盖主流 Benchmark 集成、自定义评测设计和自动化 CI/CD</description></item><item><title>LLM代码生成能力评测</title><link>https://guijiagi.com/posts/llm-code-gen-eval/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-code-gen-eval/</guid><description>LLM代码生成能力评测</description></item><item><title>LLM评测榜单可信度分析</title><link>https://guijiagi.com/posts/llm-benchmark-credibility/</link><pubDate>Sat, 27 Jun 2026 15:00:00 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测试实践：统计显著性与业务指标</title><link>https://guijiagi.com/posts/a-b-testing-for-llm/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/a-b-testing-for-llm/</guid><description>系统介绍 LLM 产品的 A/B 测试方法，涵盖实验设计、样本量计算、统计显著性检验、业务指标选择与常见陷阱。</description></item><item><title>LLM Kubernetes 部署指南：GPU 调度与弹性扩缩容</title><link>https://guijiagi.com/posts/llm-deployment-k8s/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-deployment-k8s/</guid><description>从 GPU 节点池配置、模型服务部署、自动扩缩容到推理优化，完整介绍 LLM 在 Kubernetes 上的生产级部署方案。</description></item></channel></rss>