Upload README.md

README.md

@@ -76,6 +76,14 @@ In its entirety, WRAPresentations encodes the following hierarchy for tweets:
   <img src="https://github.com/TomatenMarc/public-images/raw/main/Argument_Tree.svg" alt="Argument Tree" width="100%">
 </div>
 
+## Class Semantic Transfer to Embeddings
+
+Observing the tweet distribution within the embedding space of WRAPresentations, we noted that extended pre-training via contrastive learning led 
+to denser emergence of the expected class sectors compared to the embeddings of BERTweet, as shown in the following figure.
+<div align="center">
+  <img src="https://github.com/TomatenMarc/public-images/raw/main/sector_purity_coordinates.svg" alt="Argument Tree" width="100%">
+</div>
+
 
 ## Usage (Sentence-Transformers)