Removed latex equation and added TOC

README.md

@@ -1,3 +1,7 @@
+---
+gitea: none
+include_toc: true
+---
 
 # Prompt-based methods for Dialog State Tracking    
     
@@ -269,12 +273,8 @@ In the previous section, only a single *value-based* prompt is used at training
 
 A separate prompt ensemble model is trained for each data split to evaluate the performance of multi-prompt methods in low-resource scenarios. Edit the [train_prompting.sh](prompt-learning/train_prompting.sh) file to add `--with_prompt_ensemble` flag for training with multiple prompt functions.  
 
-The probability of slot $s_{t}$ on multiple prompt functions are calculated using:
+The probability of the generated slot (for loss) on multiple prompt functions is calculated by weighted averaging the probability from each prompt function.
 
-$$  
-P\left(s_{t} \mid c_{t}\right)=\sum_{k}^{|K|} \alpha_{k} * P\left(s_{t} \mid c_{t}, f_{k}\left(v_{t}\right)\right)  
-$$
-where $|K|$ represents the number of prompt functions, $f_{k}$ is the $k$-th prompt function, $\alpha_{k}$ is the weight of prompt $k$. The prompt weight $\alpha_{k}$ is set to `0.25` for all prompt functions. The loss $L$ for prompt ensemble training is calculated using the above function.
 
 Run the training script as before after adding the `--with_prompt_ensemble` flag:
 ```shell