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@@ -81,8 +81,8 @@ Exploring Refusal Loss Landscapes </title>
 <p>Current transformer-based LLMs will return different responses to the same query due to the randomness of 
   autoregressive sampling-based generation. With this randomness, it is an 
   interesting phenomenon that a malicious user query will sometimes be rejected by the target LLM, but 
-  sometimes be able to bypass the safety guardrail. Based on this observation, for a given LLM $$T_\theta$$ parameterized with $\theta$, we 
-  define the refusal loss function $\phi_\theta(x)$ for a given input user query $x$ as below:
+  sometimes be able to bypass the safety guardrail. Based on this observation, for a given LLM <p>$T_\theta$</p> 
+  parameterized with $\theta$, we define the refusal loss function $\phi_\theta(x)$ for a given input user query $x$ as below:
 </p>
 
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