diff --git a/feed.xml b/feed.xml
index 77b1a76..93b953c 100644
--- a/feed.xml
+++ b/feed.xml
@@ -1,4 +1,4 @@
-<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.5.2">Jekyll</generator><link href="https://www.dgl.ai/feed.xml" rel="self" type="application/atom+xml" /><link href="https://www.dgl.ai/" rel="alternate" type="text/html" /><updated>2024-05-08T06:42:47+00:00</updated><id>https://www.dgl.ai/feed.xml</id><title type="html">Deep Graph Library</title><subtitle>Easy Deep Learning on Graphs</subtitle><entry><title type="html">DGL 2.1: GPU Acceleration for Your GNN Data Pipeline</title><link href="https://www.dgl.ai/release/2024/03/06/release.html" rel="alternate" type="text/html" title="DGL 2.1: GPU Acceleration for Your GNN Data Pipeline" /><published>2024-03-06T00:00:00+00:00</published><updated>2024-03-06T00:00:00+00:00</updated><id>https://www.dgl.ai/release/2024/03/06/release</id><content type="html" xml:base="https://www.dgl.ai/release/2024/03/06/release.html">&lt;p&gt;We are happy to announce the release of DGL 2.1. In this release, we are making
+<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.5.2">Jekyll</generator><link href="https://www.dgl.ai/feed.xml" rel="self" type="application/atom+xml" /><link href="https://www.dgl.ai/" rel="alternate" type="text/html" /><updated>2024-05-11T00:54:20+00:00</updated><id>https://www.dgl.ai/feed.xml</id><title type="html">Deep Graph Library</title><subtitle>Easy Deep Learning on Graphs</subtitle><entry><title type="html">DGL 2.1: GPU Acceleration for Your GNN Data Pipeline</title><link href="https://www.dgl.ai/release/2024/03/06/release.html" rel="alternate" type="text/html" title="DGL 2.1: GPU Acceleration for Your GNN Data Pipeline" /><published>2024-03-06T00:00:00+00:00</published><updated>2024-03-06T00:00:00+00:00</updated><id>https://www.dgl.ai/release/2024/03/06/release</id><content type="html" xml:base="https://www.dgl.ai/release/2024/03/06/release.html">&lt;p&gt;We are happy to announce the release of DGL 2.1. In this release, we are making
 GNN data loading lightning fast. We introduce GPU acceleration for the whole GNN
 data loading pipeline in GraphBolt, including the graph sampling and feature
 fetching stages.&lt;/p&gt;
diff --git a/feed/blog.xml b/feed/blog.xml
index 160f956..731d6ee 100644
--- a/feed/blog.xml
+++ b/feed/blog.xml
@@ -1,4 +1,4 @@
-<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.5.2">Jekyll</generator><link href="https://www.dgl.ai/feed/blog.xml" rel="self" type="application/atom+xml" /><link href="https://www.dgl.ai/" rel="alternate" type="text/html" /><updated>2024-05-08T06:42:47+00:00</updated><id>https://www.dgl.ai/feed/blog.xml</id><title type="html">Deep Graph Library | Blog</title><subtitle>Easy Deep Learning on Graphs</subtitle><entry><title type="html">Improving Graph Neural Networks via Network-in-network Architecture</title><link href="https://www.dgl.ai/blog/2022/11/28/ngnn.html" rel="alternate" type="text/html" title="Improving Graph Neural Networks via Network-in-network Architecture" /><published>2022-11-28T00:00:00+00:00</published><updated>2022-11-28T00:00:00+00:00</updated><id>https://www.dgl.ai/blog/2022/11/28/ngnn</id><content type="html" xml:base="https://www.dgl.ai/blog/2022/11/28/ngnn.html">&lt;p&gt;As Graph Neural Networks (GNNs) has become increasingly popular, there is a
+<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.5.2">Jekyll</generator><link href="https://www.dgl.ai/feed/blog.xml" rel="self" type="application/atom+xml" /><link href="https://www.dgl.ai/" rel="alternate" type="text/html" /><updated>2024-05-11T00:54:20+00:00</updated><id>https://www.dgl.ai/feed/blog.xml</id><title type="html">Deep Graph Library | Blog</title><subtitle>Easy Deep Learning on Graphs</subtitle><entry><title type="html">Improving Graph Neural Networks via Network-in-network Architecture</title><link href="https://www.dgl.ai/blog/2022/11/28/ngnn.html" rel="alternate" type="text/html" title="Improving Graph Neural Networks via Network-in-network Architecture" /><published>2022-11-28T00:00:00+00:00</published><updated>2022-11-28T00:00:00+00:00</updated><id>https://www.dgl.ai/blog/2022/11/28/ngnn</id><content type="html" xml:base="https://www.dgl.ai/blog/2022/11/28/ngnn.html">&lt;p&gt;As Graph Neural Networks (GNNs) has become increasingly popular, there is a
 wide interest of designing deeper GNN architecture. However, deep GNNs suffer
 from the &lt;em&gt;oversmoothing&lt;/em&gt; issue where the learnt node representations quickly
 become indistinguishable with more layers. This blog features a simple yet
diff --git a/jekyll/_includes/install_content.html b/jekyll/_includes/install_content.html
index b62a0d8..f902b0f 100644
--- a/jekyll/_includes/install_content.html
+++ b/jekyll/_includes/install_content.html
@@ -198,9 +198,6 @@ <h2 class="themeix-section-title text-center">Installation</h2>
     },
     computed: {
       path_value: function () {
-        if (this.button_pytorch === '2.3.x') {
-          return "# `torchdata`(the key dependency of DGL) is not compatible with PyTorch 2.3.0. Please use PyTorch 2.2.x or 2.1.x instead."
-        }
         if (this.button_os === 'Mac') {
           var cmd = (this.button_pkg === 'Conda(Stable)') ? conda_path('None', this.button_os, this.button_pytorch) : "pip install dgl -f https://data.dgl.ai/wheels/repo.html";
           if (this.button_pkg === 'Pip(Nightly Build)') {
diff --git a/pages/start.html b/pages/start.html
index d0501da..4f97f2b 100644
--- a/pages/start.html
+++ b/pages/start.html
@@ -669,9 +669,6 @@ <h2 id="using-dgl-with-sagemaker">Using DGL with SageMaker</h2>
     },
     computed: {
       path_value: function () {
-        if (this.button_pytorch === '2.3.x') {
-          return "# `torchdata`(the key dependency of DGL) is not compatible with PyTorch 2.3.0. Please use PyTorch 2.2.x or 2.1.x instead."
-        }
         if (this.button_os === 'Mac') {
           var cmd = (this.button_pkg === 'Conda(Stable)') ? conda_path('None', this.button_os, this.button_pytorch) : "pip install dgl -f https://data.dgl.ai/wheels/repo.html";
           if (this.button_pkg === 'Pip(Nightly Build)') {