updated CoRL acceptances

Author: abajcsy

publications.html

@@ -71,42 +71,7 @@
             </tr>
 
 
-            <td style="padding-left:20px;padding-bottom:20px;width:15%;vertical-align:middle">
-              <img src="paper_imgs/gupta_2025.png"  style="border-radius:5%/10%;width:200px">
-            </td>
-            <td style="padding-left:35px;padding-bottom:20px;width:100%;vertical-align:left">
-                <papertitle>Adapting by Analogy: OOD Generalization of Visuomotor Policies via Functional Correspondence</papertitle>
-                <br>
-                  P. Gupta, H. Admoni, A. Bajcsy
-                <br>
-                <em>arXiv</em>, 2025
-                <br>
-                <br>
-                <a class="button-paper" href="https://arxiv.org/abs/2506.12678"><i class="fa fa-file-text" aria-hidden="true"></i> paper</a>
-                <!-- &nbsp -->
-                <!-- <a class="button-website" href="https://cmu-intentlab.github.io/UNISafe/"><i class="fa fa-external-link"></i> website</a> -->
-                <p></p>
-              </td>
-            </tr>
-
-
-            <td style="padding-left:20px;padding-bottom:20px;width:15%;vertical-align:middle">
-              <img src="paper_imgs/seo_2025_UNISafe.gif"  style="border-radius:5%/10%;width:200px">
-            </td>
-            <td style="padding-left:35px;padding-bottom:20px;width:100%;vertical-align:left">
-                <papertitle>UNISafe: Uncertainty-aware Latent Safety Filters for Avoiding Out-of-Distribution Failures</papertitle>
-                <br>
-                  J. Seo, K. Nakamura, A. Bajcsy
-                <br>
-                <em>arXiv</em>, 2025
-                <br>
-                <br>
-                <a class="button-paper" href="https://arxiv.org/abs/2505.00779"><i class="fa fa-file-text" aria-hidden="true"></i> paper</a>
-                &nbsp
-                <a class="button-website" href="https://cmu-intentlab.github.io/UNISafe/"><i class="fa fa-external-link"></i> website</a>
-                <p></p>
-              </td>
-            </tr>
+  
 
             <td style="padding-left:20px;padding-bottom:20px;width:15%;vertical-align:middle">
               <img src="paper_imgs/sagheb_2025.png"  style="border-radius:5%/10%;width:200px">
@@ -206,6 +171,44 @@
           <table style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;"><tbody>
 
           <!-- begin publication list --> 
+            <td style="padding-left:20px;padding-bottom:20px;width:15%;vertical-align:middle">
+              <img src="paper_imgs/gupta_2025.png"  style="border-radius:5%/10%;width:200px">
+            </td>
+            <td style="padding-left:35px;padding-bottom:20px;width:100%;vertical-align:left">
+                <papertitle>Adapting by Analogy: OOD Generalization of Visuomotor Policies via Functional Correspondence</papertitle>
+                <br>
+                  P. Gupta, H. Admoni, A. Bajcsy
+                <br>
+                <em>Conference on Robot Learning (CoRL)</em>, 2025
+                <br>
+                <br>
+                <a class="button-paper" href="https://arxiv.org/abs/2506.12678"><i class="fa fa-file-text" aria-hidden="true"></i> paper</a>
+                <!-- &nbsp -->
+                <!-- <a class="button-website" href="https://cmu-intentlab.github.io/UNISafe/"><i class="fa fa-external-link"></i> website</a> -->
+                <p></p>
+              </td>
+            </tr>
+
+
+            <td style="padding-left:20px;padding-bottom:20px;width:15%;vertical-align:middle">
+              <img src="paper_imgs/seo_2025_UNISafe.gif"  style="border-radius:5%/10%;width:200px">
+            </td>
+            <td style="padding-left:35px;padding-bottom:20px;width:100%;vertical-align:left">
+                <papertitle>UNISafe: Uncertainty-aware Latent Safety Filters for Avoiding Out-of-Distribution Failures</papertitle>
+                <br>
+                  J. Seo, K. Nakamura, A. Bajcsy
+                <br>
+                <em>Conference on Robot Learning (CoRL)</em>, 2025
+                <br>
+                <br>
+                <a class="button-paper" href="https://arxiv.org/abs/2505.00779"><i class="fa fa-file-text" aria-hidden="true"></i> paper</a>
+                &nbsp
+                <a class="button-website" href="https://cmu-intentlab.github.io/UNISafe/"><i class="fa fa-external-link"></i> website</a>
+                <p></p>
+              </td>
+            </tr>
+
+
           <td style="padding-left:20px;padding-bottom:20px;width:15%;vertical-align:middle">
             <img src="paper_imgs/jeong_2024_v2.png" style="border-radius:5%/10%;width:200px">
           </td>