This post is a brief summary about the paper that I read for my study and curiosity, so I shortly arrange the content of the paper, titled RichRAG: Crafting Rich Reponses for Multi-faceted Queries in Retrieval-Augmented Generation (Wang et al., arXiv 2024), that I read and studied.

They proposed the RAG,called RichRAG, for rich and comprehensive response.

The RichRAG consists of sub-aspect explorer, the multi-faceted retriever, and the generative list-wise ranker.

For detailed experiment and explanation, refer to the paper, titled RichRAG: Crafting Rich Reponses for Multi-faceted Queries in Retrieval-Augmented Generation (Wang et al., arXiv 2024)

Reference

• Paper
  • ArXiv Version: RichRAG: Crafting Rich Reponses for Multi-faceted Queries in Retrieval-Augmented Generation (Wang et al., arXiv 2024)
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