Update README.md

README.md

@@ -12,15 +12,19 @@ model_index:
 - name: kpr-bert-base-uncased
   results:
 ---
-# kpr-bert-base-uncased
+
+# Knowledgeable Embedding: kpr-bert-base-uncased
 
 ## Introduction
 
+**Injecting dynamically updatable entity knowledge into embeddings to enhance RAG**
+
 A key limitation of large language models (LLMs) is their inability to capture less-frequent or up-to-date entity knowledge, often leading to factual inaccuracies and hallucinations. Retrieval-augmented generation (RAG), which incorporates external knowledge through retrieval, is a common approach to mitigate this issue.
 
 Although RAG typically relies on embedding-based retrieval, the embedding models themselves are also based on language models and therefore struggle with queries involving less-frequent entities, often failing to retrieve the crucial knowledge needed to overcome this limitation.
 
-**Knowledgeable Passage Retriever** enhances the performance with such queries by injecting real-world entity knowledge into embeddings, making them more *knowledgeable*.
+**Knowledgeable Embedding** enhances the performance with such queries by injecting real-world entity knowledge into embeddings, making them more *knowledgeable*.
+
 **The entity knowledge is pluggable and can be dynamically updated with ease.**
 
 For more details, refer to [our GitHub repository](https://github.com/knowledgeable-embedding/knowledgeable-embedding).