Update index.html

index.html

@@ -196,14 +196,15 @@
 <!-- Overview -->
 <section class="section">
   <div class="container is-max-desktop">
-    <h2 class="title is-3">Method Overview of BEYOND</h2>
+    <h2 class="title is-3">Method Overview of GREAT Score</h2>
     <div class="columns is-centered">
       <div class="column container-centered">
-        <img src="./static/images/overview.png" alt="Method Overview of BEYOND"/>
-        <p><strong>Figure 2. Overview of BEYOND.</strong> First, we augment the input image to obtain a bunch of its neighbors. Then, we
-          perform the label consistency detection mechanism on the classifier’s prediction of the input image and that of neighbors predicted by
-          SSL’s classification head. Meanwhile, the representation similarity mechanism employs cosine distance to measure the similarity among
-          the input image and its neighbors. Finally, The input image with poor label consistency or representation similarity is flagged as AE.</p>
+        <img src="./static/images/GREAT_Score_overview.png" alt="Method Overview of GREAT Score"/>
+        <p><strong>Figure 1. Overview of GREAT Score.</strong> The process involves three main steps: 
+        (1) Data Generation: We use a generative model to create synthetic samples. 
+        (2) Local Robustness Evaluation: For each generated sample, we calculate a local robustness score based on the classifier's confidence. 
+        (3) Global Robustness Estimation: We aggregate the local scores to estimate the overall robustness of the classifier. 
+        This method provides a certified lower bound on the true global robustness without requiring access to the original dataset or exhaustive adversarial attacks.</p>
       </div>
     </div>
   </div>
@@ -274,9 +275,181 @@
       </div>
     </div>
 
+
+
+  </section>
+
+
+
+  <!-- Results -->
+  <section class="section">
+    <div class="container is-max-desktop">
+      <h2 class="title is-3">GREAT Score Results</h2>
+      <div class="columns is-centered">
+        <div class="column container-centered">
+          <table class="tg" border="1" style="width:100%;">
+            <caption><strong>Table 1.</strong> Comparison of (Calibrated) GREAT Score v.s. minimal distortion found by CW attack on CIFAR-10. The results are averaged over 500 samples from StyleGAN2.</caption>
+            <thead>
+              <tr>
+                <th class="tg-amwm">Model Name</th>
+                <th class="tg-baqh">RobustBench Accuracy(%)</th>
+                <th class="tg-baqh">AutoAttack Accuracy(%)</th>
+                <th class="tg-baqh">GREAT Score</th>
+                <th class="tg-baqh">Calibrated GREAT Score</th>
+                <th class="tg-baqh">CW Distortion</th>
+              </tr>
+            </thead>
+            <tbody>
+              <tr>
+                <td class="tg-baqh">Rebuffi_extra</td>
+                <td class="tg-baqh">82.32</td>
+                <td class="tg-baqh">87.20</td>
+                <td class="tg-baqh">0.507</td>
+                <td class="tg-baqh">1.216</td>
+                <td class="tg-baqh">1.859</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Gowal_extra</td>
+                <td class="tg-baqh">80.53</td>
+                <td class="tg-baqh">85.60</td>
+                <td class="tg-baqh">0.534</td>
+                <td class="tg-baqh">1.213</td>
+                <td class="tg-baqh">1.324</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Rebuffi_70_ddpm</td>
+                <td class="tg-baqh">80.42</td>
+                <td class="tg-baqh">90.60</td>
+                <td class="tg-baqh">0.451</td>
+                <td class="tg-baqh">1.208</td>
+                <td class="tg-baqh">1.943</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Rebuffi_28_ddpm</td>
+                <td class="tg-baqh">78.80</td>
+                <td class="tg-baqh">90.00</td>
+                <td class="tg-baqh">0.424</td>
+                <td class="tg-baqh">1.214</td>
+                <td class="tg-baqh">1.796</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Augustin_WRN_extra</td>
+                <td class="tg-baqh">78.79</td>
+                <td class="tg-baqh">86.20</td>
+                <td class="tg-baqh">0.525</td>
+                <td class="tg-baqh">1.206</td>
+                <td class="tg-baqh">1.340</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Sehwag</td>
+                <td class="tg-baqh">77.24</td>
+                <td class="tg-baqh">89.20</td>
+                <td class="tg-baqh">0.227</td>
+                <td class="tg-baqh">1.143</td>
+                <td class="tg-baqh">1.392</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Augustin_WRN</td>
+                <td class="tg-baqh">76.25</td>
+                <td class="tg-baqh">86.40</td>
+                <td class="tg-baqh">0.583</td>
+                <td class="tg-baqh">1.206</td>
+                <td class="tg-baqh">1.332</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Rade</td>
+                <td class="tg-baqh">76.15</td>
+                <td class="tg-baqh">86.60</td>
+                <td class="tg-baqh">0.413</td>
+                <td class="tg-baqh">1.200</td>
+                <td class="tg-baqh">1.486</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Rebuffi_R18</td>
+                <td class="tg-baqh">75.86</td>
+                <td class="tg-baqh">87.60</td>
+                <td class="tg-baqh">0.369</td>
+                <td class="tg-baqh">1.210</td>
+                <td class="tg-baqh">1.413</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Gowal</td>
+                <td class="tg-baqh">74.50</td>
+                <td class="tg-baqh">86.40</td>
+                <td class="tg-baqh">0.124</td>
+                <td class="tg-baqh">1.116</td>
+                <td class="tg-baqh">1.253</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Sehwag_R18</td>
+                <td class="tg-baqh">74.41</td>
+                <td class="tg-baqh">88.60</td>
+                <td class="tg-baqh">0.236</td>
+                <td class="tg-baqh">1.135</td>
+                <td class="tg-baqh">1.343</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Wu2020Adversarial</td>
+                <td class="tg-baqh">73.66</td>
+                <td class="tg-baqh">84.60</td>
+                <td class="tg-baqh">0.128</td>
+                <td class="tg-baqh">1.110</td>
+                <td class="tg-baqh">1.369</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Augustin2020Adversarial</td>
+                <td class="tg-baqh">72.91</td>
+                <td class="tg-baqh">85.20</td>
+                <td class="tg-baqh">0.569</td>
+                <td class="tg-baqh">1.199</td>
+                <td class="tg-baqh">1.285</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Engstrom2019Robustness</td>
+                <td class="tg-baqh">69.24</td>
+                <td class="tg-baqh">82.20</td>
+                <td class="tg-baqh">0.160</td>
+                <td class="tg-baqh">1.020</td>
+                <td class="tg-baqh">1.084</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Rice2020Overfitting</td>
+                <td class="tg-baqh">67.68</td>
+                <td class="tg-baqh">81.80</td>
+                <td class="tg-baqh">0.152</td>
+                <td class="tg-baqh">1.040</td>
+                <td class="tg-baqh">1.097</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Rony2019Decoupling</td>
+                <td class="tg-baqh">66.44</td>
+                <td class="tg-baqh">79.20</td>
+                <td class="tg-baqh">0.275</td>
+                <td class="tg-baqh">1.101</td>
+                <td class="tg-baqh">1.165</td>
+              </tr>
+              <tr>
+                <td class="tg-baqh">Ding2020MMA</td>
+                <td class="tg-baqh">66.09</td>
+                <td class="tg-baqh">77.60</td>
+                <td class="tg-baqh">0.112</td>
+                <td class="tg-baqh">0.909</td>
+                <td class="tg-baqh">1.095</td>
+              </tr>
+            </tbody>
+        </table>
+        </div>
+      </div>
+    </div>
+  </section>
+  <!-- Results -->
+
+<!-- Model Ranking Comparison Section -->
+<section class="section">
+  <div class="container is-max-desktop">
+    <h2 class="title is-3">Model Ranking Comparison</h2>
     <div class="columns is-centered">
       <div class="column is-full-width">
-        <h3 class="title is-4">Model Ranking Comparison</h3>
         <div class="content has-text-justified">
           <table class="table is-bordered is-striped is-narrow is-hoverable is-fullwidth">
             <caption><strong>Table 2.</strong> Spearman's rank correlation coefficient on CIFAR-10 using GREAT Score, RobustBench (with test set), and Auto-Attack (with generated samples).</caption>
@@ -315,7 +488,14 @@
         </div>
       </div>
     </div>
+  </div>
+</section>
+<!-- Model Ranking Comparison Section -->
 
+<!-- GREAT Score vs CW Attack Comparison Section -->
+<section class="section">
+  <div class="container is-max-desktop">
+    <h2 class="title is-3">GREAT Score vs CW Attack Comparison</h2>
     <div class="columns is-centered">
       <div class="column container-centered">
         <div>
@@ -330,174 +510,11 @@
       </div>
     </div>
   </div>
-
-
 </section>
+<!-- GREAT Score vs CW Attack Comparison Section -->
 
 
 
-<!-- Results -->
-<section class="section">
-  <div class="container is-max-desktop">
-    <h2 class="title is-3">GREAT Score Results</h2>
-    <div class="columns is-centered">
-      <div class="column container-centered">
-        <table class="tg" border="1" style="width:100%;">
-          <caption><strong>Table 1.</strong> Comparison of (Calibrated) GREAT Score v.s. minimal distortion found by CW attack on CIFAR-10. The results are averaged over 500 samples from StyleGAN2.</caption>
-          <thead>
-            <tr>
-              <th class="tg-amwm">Model Name</th>
-              <th class="tg-baqh">RobustBench Accuracy(%)</th>
-              <th class="tg-baqh">AutoAttack Accuracy(%)</th>
-              <th class="tg-baqh">GREAT Score</th>
-              <th class="tg-baqh">Calibrated GREAT Score</th>
-              <th class="tg-baqh">CW Distortion</th>
-            </tr>
-          </thead>
-          <tbody>
-            <tr>
-              <td class="tg-baqh">Rebuffi_extra</td>
-              <td class="tg-baqh">82.32</td>
-              <td class="tg-baqh">87.20</td>
-              <td class="tg-baqh">0.507</td>
-              <td class="tg-baqh">1.216</td>
-              <td class="tg-baqh">1.859</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Gowal_extra</td>
-              <td class="tg-baqh">80.53</td>
-              <td class="tg-baqh">85.60</td>
-              <td class="tg-baqh">0.534</td>
-              <td class="tg-baqh">1.213</td>
-              <td class="tg-baqh">1.324</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Rebuffi_70_ddpm</td>
-              <td class="tg-baqh">80.42</td>
-              <td class="tg-baqh">90.60</td>
-              <td class="tg-baqh">0.451</td>
-              <td class="tg-baqh">1.208</td>
-              <td class="tg-baqh">1.943</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Rebuffi_28_ddpm</td>
-              <td class="tg-baqh">78.80</td>
-              <td class="tg-baqh">90.00</td>
-              <td class="tg-baqh">0.424</td>
-              <td class="tg-baqh">1.214</td>
-              <td class="tg-baqh">1.796</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Augustin_WRN_extra</td>
-              <td class="tg-baqh">78.79</td>
-              <td class="tg-baqh">86.20</td>
-              <td class="tg-baqh">0.525</td>
-              <td class="tg-baqh">1.206</td>
-              <td class="tg-baqh">1.340</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Sehwag</td>
-              <td class="tg-baqh">77.24</td>
-              <td class="tg-baqh">89.20</td>
-              <td class="tg-baqh">0.227</td>
-              <td class="tg-baqh">1.143</td>
-              <td class="tg-baqh">1.392</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Augustin_WRN</td>
-              <td class="tg-baqh">76.25</td>
-              <td class="tg-baqh">86.40</td>
-              <td class="tg-baqh">0.583</td>
-              <td class="tg-baqh">1.206</td>
-              <td class="tg-baqh">1.332</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Rade</td>
-              <td class="tg-baqh">76.15</td>
-              <td class="tg-baqh">86.60</td>
-              <td class="tg-baqh">0.413</td>
-              <td class="tg-baqh">1.200</td>
-              <td class="tg-baqh">1.486</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Rebuffi_R18</td>
-              <td class="tg-baqh">75.86</td>
-              <td class="tg-baqh">87.60</td>
-              <td class="tg-baqh">0.369</td>
-              <td class="tg-baqh">1.210</td>
-              <td class="tg-baqh">1.413</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Gowal</td>
-              <td class="tg-baqh">74.50</td>
-              <td class="tg-baqh">86.40</td>
-              <td class="tg-baqh">0.124</td>
-              <td class="tg-baqh">1.116</td>
-              <td class="tg-baqh">1.253</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Sehwag_R18</td>
-              <td class="tg-baqh">74.41</td>
-              <td class="tg-baqh">88.60</td>
-              <td class="tg-baqh">0.236</td>
-              <td class="tg-baqh">1.135</td>
-              <td class="tg-baqh">1.343</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Wu2020Adversarial</td>
-              <td class="tg-baqh">73.66</td>
-              <td class="tg-baqh">84.60</td>
-              <td class="tg-baqh">0.128</td>
-              <td class="tg-baqh">1.110</td>
-              <td class="tg-baqh">1.369</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Augustin2020Adversarial</td>
-              <td class="tg-baqh">72.91</td>
-              <td class="tg-baqh">85.20</td>
-              <td class="tg-baqh">0.569</td>
-              <td class="tg-baqh">1.199</td>
-              <td class="tg-baqh">1.285</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Engstrom2019Robustness</td>
-              <td class="tg-baqh">69.24</td>
-              <td class="tg-baqh">82.20</td>
-              <td class="tg-baqh">0.160</td>
-              <td class="tg-baqh">1.020</td>
-              <td class="tg-baqh">1.084</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Rice2020Overfitting</td>
-              <td class="tg-baqh">67.68</td>
-              <td class="tg-baqh">81.80</td>
-              <td class="tg-baqh">0.152</td>
-              <td class="tg-baqh">1.040</td>
-              <td class="tg-baqh">1.097</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Rony2019Decoupling</td>
-              <td class="tg-baqh">66.44</td>
-              <td class="tg-baqh">79.20</td>
-              <td class="tg-baqh">0.275</td>
-              <td class="tg-baqh">1.101</td>
-              <td class="tg-baqh">1.165</td>
-            </tr>
-            <tr>
-              <td class="tg-baqh">Ding2020MMA</td>
-              <td class="tg-baqh">66.09</td>
-              <td class="tg-baqh">77.60</td>
-              <td class="tg-baqh">0.112</td>
-              <td class="tg-baqh">0.909</td>
-              <td class="tg-baqh">1.095</td>
-            </tr>
-          </tbody>
-      </table>
-      </div>
-    </div>
-  </div>
-</section>
-<!-- Results -->