Update meme_papers.html

meme_papers.html

@@ -121,15 +121,15 @@
       <td style="padding-right: 10px;">2023</td>
       <td style="padding-right: 5px;"><a href="https://hal.science/hal-04214094v1/document" target="_blank">An In-depth Analysis of Implicit and Subtle Hate
 Speech Messages</td>
-      <td style="padding-right: 10px;">It compares different benchmark for Hate-Speech detection and highlights the facts that conventional models are not suitable for detecting a implicit/subtle hate content.</td>
+      <td style="padding-right: 10px;">It compares different benchmarks for Hate-Speech detection and highlights the facts that conventional models are not suitable for detecting a implicit/subtle hate content.</td>
       <td style="padding-right: 10px;"> Pending </td>
   </tr>
 
   <tr>
     <td>18</td>
       <td style="padding-right: 10px;">2022</td>
       <td style="padding-right: 5px;"><a href="https://arxiv.org/abs/2203.09509" target="_blank">ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection</a></td>
-      <td style="padding-right: 10px;"> *** </td>
+      <td style="padding-right: 10px;"> It is a toxic Data Creation Framework. Using LLM, it uses description-based prompting + adversarial-classifier-in-loop method to generate toxic data using a LLM.</td>
       <td style="padding-right: 10px;"> Pending </td>
   </tr>