Update README.md

README.md

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 ## Model Summary
-This is a generative model designed specifically for search query rewriting, employing a sequence-to-sequence architecture for generating reformulated queries. Its training incorporates a policy gradient algorithm to enhance performance. The model is trained with reward functions aimed at diversifying the generated queries by paraphrasing keywords. It can be integrated with sparse retrieval methods, such as bm25-based retrieval, to enhance document recall in search.
+This is a generative model designed specifically for search query rewriting, employing a sequence-to-sequence architecture for generating reformulated queries. It leverages a Reinforcement Learning framework to further boost performance, integrating a policy gradient algorithm. The model is trained with reward functions aimed at diversifying the generated queries by paraphrasing keywords. It can be integrated with sparse retrieval methods, such as bm25-based retrieval, to enhance document recall in search.
 
 ### Model Description