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 <!DOCTYPE html>
-<html>
 <head>
-  <meta charset="utf-8">
-  <meta name="description" content="DeepSeek: Advancing Open-Source Language Models">
-  <meta name="keywords" content="DeepSeek, LLM, AI">
-  <meta name="viewport" content="width=device-width, initial-scale=1">
-  <title>DeepSeek: Advancing Open-Source Language Models</title>
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-  <script src="./static/js/index.js"></script>
 </head>
 <body>
-<section class="hero">
-  <div class="hero-body">
-    <div class="container is-max-desktop">
-      <div class="columns is-centered">
-        <div class="column has-text-centered">
-          <h1 class="title is-1 publication-title">DeepSeek: Advancing Open-Source Language Models</h1>
-          <div class="is-size-5 publication-authors">
-            A collection of groundbreaking research papers in AI and language models
-          </div>
-        </div>
-      </div>
     </div>
-  </div>
-</section>
-<section class="section">
-  <div class="container is-max-desktop">
-    <!-- Abstract. -->
-    <div class="columns is-centered has-text-centered">
-      <div class="column is-four-fifths">
-        <h2 class="title is-3">Overview</h2>
-        <div class="content has-text-justified">
-          <p>
-            DeepSeek has released a series of significant papers detailing advancements in large language models (LLMs).
-            Each paper represents a step forward in making AI more capable, efficient, and accessible.
-          </p>
-        </div>
-      </div>
     </div>
-    <!--/ Abstract. -->
-    <!-- Paper Collection -->
-    <div class="columns is-centered has-text-centered">
-      <div class="column is-four-fifths">
-        <h2 class="title is-3">Research Papers</h2>
-        <!-- Paper 1 -->
-        <div class="publication-block">
-          <div class="publication-header">
-            <h3 class="title is-4">DeepSeekLLM: Scaling Open-Source Language Models with Longer-termism</h3>
-            <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
-            <div class="is-size-5 publication-authors">
-              Released: November 29, 2023
-            </div>
-          </div>
-          <div class="content has-text-justified">
-            <p>This foundational paper explores scaling laws and the trade-offs between data and model size,
-            establishing the groundwork for subsequent models.</p>
-          </div>
-        </div>
-        <!-- Paper 2 -->
-        <div class="publication-block">
-          <div class="publication-header">
-            <h3 class="title is-4">DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model</h3>
-            <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
-            <div class="is-size-5 publication-authors">
-              Released: May 2024
-            </div>
-          </div>
-          <div class="content has-text-justified">
-            <p>Introduces a Mixture-of-Experts (MoE) architecture, enhancing performance while reducing
-            training costs by 42%.</p>
-          </div>
-        </div>
-        <!-- Additional papers following same structure -->
-        <div class="publication-block">
-          <div class="publication-header">
-            <h3 class="title is-4">DeepSeek-V3 Technical Report</h3>
-            <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
-            <div class="is-size-5 publication-authors">
-              Released: December 2024
-            </div>
-          </div>
-          <div class="content has-text-justified">
-            <p>Discusses the scaling of sparse MoE networks to 671 billion parameters.</p>
-          </div>
-        </div>
-        <div class="publication-block">
-          <div class="publication-header">
-            <h3 class="title is-4">DeepSeek-R1: Incentivizing Reasoning Capability in LLMs</h3>
-            <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
-            <div class="is-size-5 publication-authors">
-              Released: January 20, 2025
-            </div>
-          </div>
-          <div class="content has-text-justified">
-            <p>Enhances reasoning capabilities through large-scale reinforcement learning.</p>
-          </div>
-        </div>
-        <div class="publication-block">
-          <div class="publication-header">
-            <h3 class="title is-4">DeepSeekMath: Pushing the Limits of Mathematical Reasoning</h3>
-            <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
-            <div class="is-size-5 publication-authors">
-              Released: April 2024
-            </div>
-          </div>
-          <div class="content has-text-justified">
-            <p>Presents methods to improve mathematical reasoning in LLMs.</p>
-          </div>
-        </div>
-        <div class="publication-block">
-          <div class="publication-header">
-            <h3 class="title is-4">DeepSeek-Prover: Advancing Theorem Proving in LLMs</h3>
-            <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
-          </div>
-          <div class="content has-text-justified">
-            <p>Focuses on enhancing theorem proving capabilities using synthetic data for training.</p>
-          </div>
-        </div>
-        <div class="publication-block">
-          <div class="publication-header">
-            <h3 class="title is-4">DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models</h3>
-            <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
-          </div>
-          <div class="content has-text-justified">
-            <p>Details advancements in code-related tasks with emphasis on open-source methodologies.</p>
-          </div>
-        </div>
-        <div class="publication-block">
-          <div class="publication-header">
-            <h3 class="title is-4">DeepSeekMoE: Advancing Mixture-of-Experts Architecture</h3>
-            <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
-          </div>
-          <div class="content has-text-justified">
-            <p>Discusses the integration and benefits of the Mixture-of-Experts approach.</p>
-          </div>
-        </div>
-      </div>
     </div>
-  </div>
-</section>
-<footer class="footer">
-  <div class="container">
-    <div class="content has-text-centered">
-      <a class="icon-link" href="https://github.com/deepseek-ai" target="_blank" class="external-link">
-        <i class="fab fa-github"></i>
-      </a>
     </div>
-    <div class="columns is-centered">
-      <div class="column is-8">
-        <div class="content">
-          <p>
-            This website is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/">Creative
-            Commons Attribution-ShareAlike 4.0 International License</a>.
-          </p>
-        </div>
-      </div>
     </div>
   </div>
-</footer>
 </body>
 </html>

 <!DOCTYPE html>
+<html lang="en">
 <head>
+  <meta charset="UTF-8">
+  <meta name="viewport" content="width=device-width, initial-scale=1.0">
+  <title>DeepSeek Papers</title>
+  <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0-beta3/css/all.min.css">
+  <style>
+    body {
+      font-family: 'Arial', sans-serif;
+      margin: 0;
+      padding: 0;
+      line-height: 1.6;
+      color: #333;
+      background-color: #f9f9f9;
+    }
+    header {
+      background: #4CAF50;
+      color: white;
+      padding: 20px 0;
+      text-align: center;
+    }
+    h1 {
+      margin: 0;
+      font-size: 2.5em;
+    }
+    .container {
+      max-width: 800px;
+      margin: 20px auto;
+      padding: 20px;
+      background: white;
+      border-radius: 8px;
+      box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+    }
+    .paper {
+      margin-bottom: 20px;
+    }
+    .paper a {
+      text-decoration: none;
+      color: #4CAF50;
+      font-weight: bold;
+    }
+    .paper a:hover {
+      text-decoration: underline;
+    }
+    .coming-soon {
+      color: #e74c3c;
+      font-size: 0.9em;
+      margin-left: 10px;
+    }
+    footer {
+      text-align: center;
+      padding: 10px 0;
+      background: #4CAF50;
+      color: white;
+      margin-top: 20px;
+    }
+  </style>
 </head>
 <body>
+  <header>
+    <h1>DeepSeek Papers</h1>
+  </header>
+  <div class="container">
+    <h2>DeepSeek Research Contributions</h2>
+    <p>Below is a list of significant papers by DeepSeek detailing advancements in large language models (LLMs). Each paper includes a brief description and highlights upcoming deep dives.</p>
+    <!-- Paper List -->
+    <div class="paper">
+      <a href="#">DeepSeekLLM: Scaling Open-Source Language Models with Longer-termism</a>
+      <span class="coming-soon">[Deep Dive Coming Soon]</span>
+      <p><strong>Release Date:</strong> November 29, 2023<br>
+      This foundational paper explores scaling laws and the trade-offs between data and model size, establishing the groundwork for subsequent models.</p>
     </div>
+    <div class="paper">
+      <a href="#">DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model</a>
+      <span class="coming-soon">[Deep Dive Coming Soon]</span>
+      <p><strong>Release Date:</strong> May 2024<br>
+      This paper introduces a Mixture-of-Experts (MoE) architecture, enhancing performance while reducing training costs by 42%.</p>
     </div>
+    <div class="paper">
+      <a href="#">DeepSeek-V3 Technical Report</a>
+      <span class="coming-soon">[Deep Dive Coming Soon]</span>
+      <p><strong>Release Date:</strong> December 2024<br>
+      This report discusses the scaling of sparse MoE networks to 671 billion parameters, utilizing mixed precision training and HPC co-design strategies.</p>
     </div>
+    <div class="paper">
+      <a href="#">DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning</a>
+      <span class="coming-soon">[Deep Dive Coming Soon]</span>
+      <p><strong>Release Date:</strong> January 20, 2025<br>
+      The R1 model enhances reasoning capabilities through large-scale reinforcement learning, competing directly with leading models like OpenAI's o1.</p>
+    </div>
+    <div class="paper">
+      <a href="#">DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models</a>
+      <span class="coming-soon">[Deep Dive Coming Soon]</span>
+      <p><strong>Release Date:</strong> April 2024<br>
+      This paper presents methods to improve mathematical reasoning in LLMs, introducing the Group Relative Policy Optimization (GRPO) algorithm.</p>
+    </div>
+    <div class="paper">
+      <a href="#">DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data</a>
+      <span class="coming-soon">[Deep Dive Coming Soon]</span>
+      <p>Focuses on enhancing theorem proving capabilities in language models using synthetic data for training.</p>
     </div>
+    <div class="paper">
+      <a href="#">DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence</a>
+      <span class="coming-soon">[Deep Dive Coming Soon]</span>
+      <p>This paper details advancements in code-related tasks with an emphasis on open-source methodologies, improving upon earlier coding models.</p>
+    </div>
+    <div class="paper">
+      <a href="#">DeepSeekMoE</a>
+      <span class="coming-soon">[Deep Dive Coming Soon]</span>
+      <p>Discusses the integration and benefits of the Mixture-of-Experts approach within the DeepSeek framework.</p>
     </div>
   </div>
+  <footer>
+    &copy; 2025 DeepSeek Research. All rights reserved.
+  </footer>
 </body>
 </html>