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index.html

@@ -91,7 +91,7 @@
             </div>
           </div>
 
-          <!-- Continue with other papers... -->
+          <!-- DeepSeek-V3 -->
           <div class="card paper-card">
             <div class="card-content">
               <h3 class="title is-4">
@@ -106,7 +106,77 @@
             </div>
           </div>
 
-          <!-- Add remaining papers following the same pattern -->
+          <!-- DeepSeek-R1 -->
+          <div class="card paper-card">
+            <div class="card-content">
+              <h3 class="title is-4">
+                DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
+                <span class="coming-soon-badge">Deep Dive Coming Soon</span>
+              </h3>
+              <p class="release-date">Released: January 20, 2025</p>
+              <p class="paper-description">
+                The R1 model builds on previous work to enhance reasoning capabilities through large-scale 
+                reinforcement learning, competing directly with leading models like OpenAI's o1.
+              </p>
+            </div>
+          </div>
+
+          <!-- DeepSeekMath -->
+          <div class="card paper-card">
+            <div class="card-content">
+              <h3 class="title is-4">
+                DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
+                <span class="coming-soon-badge">Deep Dive Coming Soon</span>
+              </h3>
+              <p class="release-date">Released: April 2024</p>
+              <p class="paper-description">
+                This paper presents methods to improve mathematical reasoning in LLMs, introducing the 
+                Group Relative Policy Optimization (GRPO) algorithm during reinforcement learning stages.
+              </p>
+            </div>
+          </div>
+
+          <!-- DeepSeek-Prover -->
+          <div class="card paper-card">
+            <div class="card-content">
+              <h3 class="title is-4">
+                DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data
+                <span class="coming-soon-badge">Deep Dive Coming Soon</span>
+              </h3>
+              <p class="paper-description">
+                Focuses on enhancing theorem proving capabilities in language models using synthetic data 
+                for training, establishing new benchmarks in automated mathematical reasoning.
+              </p>
+            </div>
+          </div>
+
+          <!-- DeepSeek-Coder-V2 -->
+          <div class="card paper-card">
+            <div class="card-content">
+              <h3 class="title is-4">
+                DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
+                <span class="coming-soon-badge">Deep Dive Coming Soon</span>
+              </h3>
+              <p class="paper-description">
+                This paper details advancements in code-related tasks with an emphasis on open-source 
+                methodologies, improving upon earlier coding models with enhanced capabilities.
+              </p>
+            </div>
+          </div>
+
+          <!-- DeepSeekMoE -->
+          <div class="card paper-card">
+            <div class="card-content">
+              <h3 class="title is-4">
+                DeepSeekMoE: Advancing Mixture-of-Experts Architecture
+                <span class="coming-soon-badge">Deep Dive Coming Soon</span>
+              </h3>
+              <p class="paper-description">
+                Discusses the integration and benefits of the Mixture-of-Experts approach within the 
+                DeepSeek framework, focusing on scalability and efficiency improvements.
+              </p>
+            </div>
+          </div>
 
         </div>
       </div>