<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[GCTTTTTT的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/GCTTTTTT</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; GCTTTTTT]]></copyright><item><title><![CDATA[远程服务器走本地代理]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/160031835</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/160031835</guid><author>GCTTTTTT</author><pubDate>Fri, 10 Apr 2026 20:57:57 +0800</pubDate><description><![CDATA[假如远程服务器的7890端口可能被占用，那么换一个映射端口。对应的vscode的设置也改为8890。]]></description><category></category></item><item><title><![CDATA[远程服务器配置codex]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/158508418</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/158508418</guid><author>GCTTTTTT</author><pubDate>Sat, 28 Feb 2026 17:48:33 +0800</pubDate><description><![CDATA[首先将本地可以登录的.codex文件夹中的auth.json文件中的内容复制到远程服务器的auth.json中完成登录；]]></description><category></category></item><item><title><![CDATA[Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models论文阅读]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/151331468</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/151331468</guid><author>GCTTTTTT</author><pubDate>Mon, 08 Sep 2025 20:39:20 +0800</pubDate><description><![CDATA[ICML 2025链式推理（CoT）被广泛采用，通过自回归地生成一系列推理步骤来增强大型语言模型（LLM）的推理能力。—>推理过程以逐步解码的令牌序列进行表示，在此过程中可能会出现错误的累积，导致推理路径和答案出现虚假内容—>为了获取用于推理的推理路径，大多数先前研究采用了检索式或Agent式范式，分别见图 2 (a) 和 (b)。然而，检索式方法，而Agent式方法则。为了解决这些问题，图约束推理（GCR）：包含三个主要组成部分：1）：构建知识图谱的以指导大型语言模型推理；2）]]></description><category></category></item><item><title><![CDATA[配乐MP3转url]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/151330969</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/151330969</guid><author>GCTTTTTT</author><pubDate>Mon, 08 Sep 2025 19:51:18 +0800</pubDate><description><![CDATA[免版税音乐下载：https://pixabay.com/zh/music/search/?]]></description><category></category></item><item><title><![CDATA[束搜索介绍]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/151327759</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/151327759</guid><author>GCTTTTTT</author><pubDate>Mon, 08 Sep 2025 17:25:33 +0800</pubDate><description><![CDATA[https://zh-v2.d2l.ai/chapter_recurrent-modern/beam-search.html]]></description><category></category></item><item><title><![CDATA[TRIPLES AS THE KEY: STRUCTURING MAKES DECOMPOSITION AND VERIFICATION EASIER IN LLM-BASED TABLEQA阅读]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/151257997</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/151257997</guid><author>GCTTTTTT</author><pubDate>Mon, 08 Sep 2025 11:34:04 +0800</pubDate><description><![CDATA[分解-推理-验证过程高度依赖于人工构造的思维链（Chain-of-Thought, CoT）提示，大语言模型难以发现其自身生成的答案中的问题。此外，由于大语言模型（LLM）的倾向，构建的验证示例会促使LLM进行自我纠正，从而导致其更容易生成相互矛盾的观点，这妨碍了TableQA中答案的准确验证。但仅依靠少量示例进行直接分解，通常会导致子问题的碎片化， 忽略了关键信息。这导致分解后的子问题与原始问题之间存在显著的语义鸿沟。]]></description><category></category></item><item><title><![CDATA[conda环境复制 自定义缓存目录]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/147756037</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/147756037</guid><author>GCTTTTTT</author><pubDate>Wed, 07 May 2025 10:50:16 +0800</pubDate><description><![CDATA[自定义缓存.cache目录。在 .bashrc中。]]></description><category></category></item><item><title><![CDATA[反向传播思想]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/147400921</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/147400921</guid><author>GCTTTTTT</author><pubDate>Mon, 21 Apr 2025 20:11:19 +0800</pubDate><description><![CDATA[根据神经网络输出的答案与正确答案之间的误差（损失函数算的损失）不断调整网络的参数。===>提前停止策略（early stopping)===>如果训练集误差↓ 的同时验证集的误差在↑。调整的程度受学习率的制约 — >控制参数调整。算出L对参数w和L对参数b的偏导（即为梯度）训练集用于调整参数，验证集用于估算误差。参数  <  - 参数 - 学习率*梯度。②算出梯度后沿梯度的反方向更新两参数。可以算出L对w和L对b的偏导（梯度）如此循环即可对w和b参数进行迭代更新。此时L = （1.4-0.8）]]></description><category></category></item><item><title><![CDATA[“Mac应用”已损坏，打不开解决办法]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/146444989</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/146444989</guid><author>GCTTTTTT</author><pubDate>Sat, 22 Mar 2025 19:26:04 +0800</pubDate><description><![CDATA[“Mac应用”已损坏，打不开解决办法]]></description><category></category></item><item><title><![CDATA[linux日常常用命令（AI向）]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/144544117</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/144544117</guid><author>GCTTTTTT</author><pubDate>Tue, 17 Dec 2024 20:45:26 +0800</pubDate><description><![CDATA[删除***用户的所有python进程。列出“***”用户的进程信息。]]></description><category></category></item><item><title><![CDATA[git add和git commit了大文件导致上传不到github的撤销操作]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/144173838</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/144173838</guid><author>GCTTTTTT</author><pubDate>Sun, 01 Dec 2024 19:51:24 +0800</pubDate><description><![CDATA[在 .gitignore 配置好之后，你可以使用 git status 来确认文件是否被正确忽略。如果文件已被添加到 Git 跟踪中（即已被提交或暂存），Git 仍然会继续跟踪它们，即使你把它们添加到 .gitignore 中。然后需要设置.gitignore文件来忽略掉大文件后重新git add 和git commit。撤销git add和git commit操作（对于修改过的代码无影响）HEAD^代表撤销最近的一个，如果有多个就reset多几次。然后再git commit和git push就可以了。]]></description><category></category></item><item><title><![CDATA[vscode中将文本文件中的‘\n‘替换为真正的换行]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/142462865</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/142462865</guid><author>GCTTTTTT</author><pubDate>Mon, 23 Sep 2024 17:01:04 +0800</pubDate><description><![CDATA[vscode中将文本文件中的'\n'替换为真正的换行]]></description><category></category></item><item><title><![CDATA[pip下载包太慢了]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/140533924</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/140533924</guid><author>GCTTTTTT</author><pubDate>Thu, 18 Jul 2024 21:45:01 +0800</pubDate><description><![CDATA[pip下载包太慢了]]></description><category></category></item><item><title><![CDATA[python调用接口]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/140215230</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/140215230</guid><author>GCTTTTTT</author><pubDate>Fri, 05 Jul 2024 17:49:58 +0800</pubDate><description><![CDATA[python调用接口api]]></description><category></category></item><item><title><![CDATA[vscode使用ssh连接远程服务器]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/140204412</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/140204412</guid><author>GCTTTTTT</author><pubDate>Fri, 05 Jul 2024 12:00:11 +0800</pubDate><description><![CDATA[vscode使用ssh连接远程服务器]]></description><category></category></item><item><title><![CDATA[Knowledgeable Preference Alignment for LLMs in Domain-specific Question Answering 论文阅读]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/136652998</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/136652998</guid><author>GCTTTTTT</author><pubDate>Tue, 12 Mar 2024 18:05:40 +0800</pubDate><description><![CDATA[近年来，大语言模型（LLM）的发展引起了学术界和工业界的广泛关注。将LLM部署到真实场景是当前互联网行业的重点方向之一。在本文中，我们提出了一种将LLM应用于特定领域问答（QA）的新颖管道，其中结合了领域知识图（KG），解决了LLM应用的一个重要方向。作为一个现实世界的应用程序，LLM生成的内容应该是用户友好的，以便为客户提供服务。此外，该模型需要正确利用领域知识来生成可靠的答案。这两个问题是LLM申请的两大难点，单纯的微调并不能充分解决。我们认为这两个需求可以统一为模型偏好问题。]]></description><category></category></item><item><title><![CDATA[linux中git暂存，提交，上传到github]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/136588589</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/136588589</guid><author>GCTTTTTT</author><pubDate>Sat, 09 Mar 2024 18:39:25 +0800</pubDate><description><![CDATA[将id_rsa.pub内容设置到github中。后面是ssh地址 github中复制。从本地仓库push到远程仓库。查看id_rsa.pub。origin为名称，可改。]]></description><category></category></item><item><title><![CDATA[linux中conda环境下安装tensorflow-gpu以及报错问题解决]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/136261643</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/136261643</guid><author>GCTTTTTT</author><pubDate>Fri, 23 Feb 2024 18:15:39 +0800</pubDate><description><![CDATA[测试是否可以使用gpu：python若输出True则可使用gpu，False则不行。]]></description><category></category></item><item><title><![CDATA[Bert下载和使用（以bert-base-uncased为例）]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/136055023</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/136055023</guid><author>GCTTTTTT</author><pubDate>Tue, 06 Feb 2024 12:55:28 +0800</pubDate><description><![CDATA[下载config.json和pytorch_model.bin。在huggingface（]]></description><category></category></item><item><title><![CDATA[JupyterLab 更换内核 使用 conda 虚拟环境]]></title><link>https://blog.youkuaiyun.com/GCTTTTTT/article/details/136030367</link><guid>https://blog.youkuaiyun.com/GCTTTTTT/article/details/136030367</guid><author>GCTTTTTT</author><pubDate>Sun, 04 Feb 2024 18:02:36 +0800</pubDate><description><![CDATA[python -m ipykernel install --user --name 虚拟环境名称 --display-name 虚拟环境名称。]]></description><category></category></item></channel></rss>