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@@ -189,9 +189,8 @@ <h1 class="title is-1 publication-title">TableLlama: Towards Open Large Generali
             <!-- <h2 class="title is-3">Introduction</h2> -->
             <div class="content has-text-justified">
               <p>
-                In this work, we proposed <b>TableLlama</b> and <b>TableInstruct</b>, which are (up to Nov 2023) the
-                first
-                <b>open-source generalist model</b> and <b>dataset</b> for <b>tables</b>. Everything is
+                In this work, we introduce <b>TableLlama</b> and <b>TableInstruct</b>, the first large
+                <b>open-source generalist model</b> and <b>instruction tuning dataset</b> for <b>tables</b>. Everything is
                 <b>open-source</b> right now!
               </p>
               <p>
@@ -203,7 +202,7 @@ <h1 class="title is-1 publication-title">TableLlama: Towards Open Large Generali
                 <li>All data items in <b>TableInstruct</b> are collected from real tables and real tasks;</li>
                 <!-- <li>Each task in <b>TableInstruct</b> is a realistic task that can be applied to real-world scenarios.</li> -->
                 <li><b>TableInstruct</b> provided both in-domain training tasks to empower the model with fundamental
-                  table understanding abilities, and in & out-of-domain evaluation tasks to test the model’s
+                  table understanding abilities, and in-domain & out-of-domain evaluation tasks to test the model’s
                   generalization and high-level reasoning ability.</li>
               </ul>
               </p>
@@ -784,4 +783,4 @@ <h2 class="title">Reference</h2>
 
 </body>
 
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