Update index.html

index.html

@@ -76,7 +76,7 @@ This phenomenon could hamper scenarios requiring accurate uncertainty estimation
 </div>
 </div>
 
-<h3 id="calibration-metrics">Calibration Metrics</h3>
+<h3 id="refusal-loss">Calibration Metrics</h3>
 <p>Objectively, researchers utilize <strong>Calibration Metrics</strong> to measure the calibration error for a model, for example,
 Expected Calibration Error (ECE), Static Calibration Error (SCE), Adaptive Calibration Error (ACE), etc.</p>
 
@@ -84,14 +84,14 @@ Expected Calibration Error (ECE), Static Calibration Error (SCE), Adaptive Calib
 <div><img id="jailbreak-intro-img" src="images/metrics/intro-metric-example.png" /></div>
 </div>
 
-<div id="calibration-metrics-formula" class="container">
-<div id="calibration-metrics-formula-list" class="row align-items-center formula-list">
+<div id="refusal-loss-formula" class="container">
+<div id="refusal-loss-formula-list" class="row align-items-center formula-list">
   <a href="#ECE-formula" class="selected">Refusal Loss</a>
   <a href="#SCE-formula">Refusal Loss Approximation</a>
   <a href="#ACE-formula">Gradient Estimation</a>
   <div style="clear: both"></div>
 </div>
-<div id="calibration-metrics-formula-content" class="row align-items-center">
+<div id="refusal-loss-formula-content" class="row align-items-center">
   <span id="ECE-formula" class="formula" style="">$$\displaystyle \phi_\theta(x)=1-\mathbb{E}_{y \sim T_\theta(x)} JB(y)$$</span>
   <span id="SCE-formula" class="formula" style="display: none;">$$\displaystyle f_\theta(x)=1-\frac{1}{N}\sum_{i=1}^N JB(y_i)$$</span>
   <span id="ACE-formula" class="formula" style="display: none;">$$\displaystyle \text{ACE}=\frac{1}{KR}\sum_{k=1}^{K}\sum_{r=1}^{R}|\text{acc}(r,k)-\text{conf}(r,k)|$$</span>