Update README.md

README.md

@@ -69,6 +69,53 @@ Explore LWM concepts and applications in this compact video series:
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+### 🎥 LWM Tutorial Series
+
+Explore LWM concepts and applications in this compact video series:
+
+<table>
+  <tr>
+    <td align="center">
+      <a href="https://www.youtube.com/watch?v=3sxJR86EFOo" target="_blank">
+        <img src="https://img.youtube.com/vi/3sxJR86EFOo/0.jpg" width="180"/>
+        <div style="margin-top:4px;padding:4px 12px;background:#f97316;color:white;border-radius:6px;font-weight:600;">▶ Watch</div>
+      </a>
+    </td>
+    <td align="center">
+      <a href="https://www.youtube.com/watch?v=Coqcya9NzFs" target="_blank">
+        <img src="https://img.youtube.com/vi/Coqcya9NzFs/0.jpg" width="180"/>
+        <div style="margin-top:4px;padding:4px 12px;background:#f97316;color:white;border-radius:6px;font-weight:600;">▶ Watch</div>
+      </a>
+    </td>
+    <td align="center">
+      <a href="https://www.youtube.com/watch?v=e9KvAXMUuQg" target="_blank">
+        <img src="https://img.youtube.com/vi/e9KvAXMUuQg/0.jpg" width="180"/>
+        <div style="margin-top:4px;padding:4px 12px;background:#f97316;color:white;border-radius:6px;font-weight:600;">▶ Watch</div>
+      </a>
+    </td>
+  </tr>
+  <tr>
+    <td align="center">
+      <a href="https://www.youtube.com/watch?v=ZB5WVvo6q6U" target="_blank">
+        <img src="https://img.youtube.com/vi/ZB5WVvo6q6U/0.jpg" width="180"/>
+        <div style="margin-top:4px;padding:4px 12px;background:#f97316;color:white;border-radius:6px;font-weight:600;">▶ Watch</div>
+      </a>
+    </td>
+    <td align="center">
+      <a href="https://www.youtube.com/watch?v=5oNnJjos0mo" target="_blank">
+        <img src="https://img.youtube.com/vi/5oNnJjos0mo/0.jpg" width="180"/>
+        <div style="margin-top:4px;padding:4px 12px;background:#f97316;color:white;border-radius:6px;font-weight:600;">▶ Watch</div>
+      </a>
+    </td>
+    <td align="center">
+      <a href="https://www.youtube.com/watch?v=_RObWck3MMw" target="_blank">
+        <img src="https://img.youtube.com/vi/_RObWck3MMw/0.jpg" width="180"/>
+        <div style="margin-top:4px;padding:4px 12px;background:#f97316;color:white;border-radius:6px;font-weight:600;">▶ Watch</div>
+      </a>
+    </td>
+  </tr>
+</table>
+
 ### **How is LWM 1.1 built?**  
 
 LWM 1.1 is a **transformer-based architecture** designed to model **spatial and frequency dependencies** in wireless channel data. It utilizes an enhanced **Masked Channel Modeling (MCM)** pretraining approach, with an increased masking ratio to improve feature learning and generalization. The introduction of **2D patch segmentation** allows the model to jointly process spatial (antenna) and frequency (subcarrier) relationships, providing a more structured representation of the channel. Additionally, **bucket-based batching** is employed to efficiently handle variable-sized inputs without excessive padding, ensuring memory-efficient training and inference. These modifications enable LWM 1.1 to extract meaningful embeddings from a wide range of wireless scenarios, improving its applicability across different system configurations.