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@@ -62,7 +62,7 @@ our proposed framework <strong>Neural Clamping</strong>, which employs a simple
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  transformation on a pre-trained classifier. We also provide other calibration approaches
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  (e.g., temperature scaling) to compare with Neural Clamping.</p>
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- <h2 id="what-is-calibration">What is Calibration?</h2>
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  <p>Neural Network Calibration seeks to make model prediction align with its true correctness likelihood.
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  A well-calibrated model should provide accurate predictions and reliable confidence when making inferences. On the
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  contrary, a poor calibration model would have a wide gap between its accuracy and average confidence level.
 
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  transformation on a pre-trained classifier. We also provide other calibration approaches
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  (e.g., temperature scaling) to compare with Neural Clamping.</p>
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+ <h2 id="what-is-jailbreak">What is Jailbreak?</h2>
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  <p>Neural Network Calibration seeks to make model prediction align with its true correctness likelihood.
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  A well-calibrated model should provide accurate predictions and reliable confidence when making inferences. On the
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  contrary, a poor calibration model would have a wide gap between its accuracy and average confidence level.