update website paper link to be the latest version

_site/feed.xml

@@ -1 +1 @@
-<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="4.2.2">Jekyll</generator><link href="http://localhost:4000/feed.xml" rel="self" type="application/atom+xml" /><link href="http://localhost:4000/" rel="alternate" type="text/html" /><updated>2023-11-05T00:59:27-05:00</updated><id>http://localhost:4000/feed.xml</id><title type="html">AMAGO</title><subtitle>A simple and scalable agent for sequence-based RL</subtitle></feed>
+<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="4.2.2">Jekyll</generator><link href="http://localhost:4000/feed.xml" rel="self" type="application/atom+xml" /><link href="http://localhost:4000/" rel="alternate" type="text/html" /><updated>2023-11-05T01:27:22-05:00</updated><id>http://localhost:4000/feed.xml</id><title type="html">AMAGO</title><subtitle>A simple and scalable agent for sequence-based RL</subtitle></feed>

_site/index.html

@@ -157,7 +157,7 @@ <h2>
     <a href="https://www.utexas.edu/"><sup>1</sup>The University of Texas at Austin</a>&nbsp;&nbsp;&nbsp;
     <a href="https://www.nvidia.com/en-us/research/"><sup>2</sup>NVIDIA Research</a>&nbsp;&nbsp;&nbsp;
   </h2>
-<h2><a href="https://arxiv.org/abs/2310.09971v1">Paper</a>&nbsp; | &nbsp;<a href="https://github.com/UT-Austin-RPL/amago">Code</a></h2>
+<h2><a href="https://arxiv.org/abs/2310.09971">Paper</a>&nbsp; | &nbsp;<a href="https://github.com/UT-Austin-RPL/amago">Code</a></h2>
   </center>
 
  <center><p><span style="font-size:20px;"></span></p></center>
@@ -276,7 +276,7 @@ <h4>
 
 <br /><br />
 
-Finally, we evaluate AMAGO in the procedurally generated worlds of <a href="https://arxiv.org/abs/2109.06780">Crafter</a>. Instructions are strings from a closed vocabulary of Crafter's achievement system, with added goals for navigation and block placement. Our agents need to generalize over thousands of unique goals in previously unseen environments, creating a highly general instruction-following agent.
+Finally, we evaluate AMAGO in the procedurally generated worlds of <a href="https://arxiv.org/abs/2109.06780">Crafter</a>. Instructions are strings from a closed vocabulary of Crafter's achievement system, with added goals for navigation and block placement.
 
 </h4>
 

index.markdown

@@ -168,7 +168,7 @@ highlight {
     <a href="https://www.utexas.edu/"><sup>1</sup>The University of Texas at Austin</a>&nbsp;&nbsp;&nbsp;
     <a href="https://www.nvidia.com/en-us/research/"><sup>2</sup>NVIDIA Research</a>&nbsp;&nbsp;&nbsp;
   </h2>
-<h2><a href="https://arxiv.org/abs/2310.09971v1">Paper</a>&nbsp; | &nbsp;<a href="https://github.com/UT-Austin-RPL/amago">Code</a></h2>
+<h2><a href="https://arxiv.org/abs/2310.09971">Paper</a>&nbsp; | &nbsp;<a href="https://github.com/UT-Austin-RPL/amago">Code</a></h2>
   </center>
 
  <center><p><span style="font-size:20px;"></span></p></center>
@@ -287,7 +287,7 @@ AMAGO handles meta-learning as a simple extension of zero-shot generalization, a
 
 <br><br>
 
-Finally, we evaluate AMAGO in the procedurally generated worlds of <a href="https://arxiv.org/abs/2109.06780">Crafter</a>. Instructions are strings from a closed vocabulary of Crafter's achievement system, with added goals for navigation and block placement. Our agents need to generalize over thousands of unique goals in previously unseen environments, creating a highly general instruction-following agent.
+Finally, we evaluate AMAGO in the procedurally generated worlds of <a href="https://arxiv.org/abs/2109.06780">Crafter</a>. Instructions are strings from a closed vocabulary of Crafter's achievement system, with added goals for navigation and block placement.
 
 </h4>