DRAGIN addresses the limitations of current dynamic RAG (Retrieval Augmented Generation) methods by introducing a novel approach for real-time decision-making on retrieval timing and content.

Mar 15, 2024 · To overcome these limitations, we introduce a new framework, DRAGIN, i.e., Dynamic Retrieval Augmented Generation based on the real-time Information Needs of LLMs.

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3 days ago · Our framework is specifically designed to make decisions on when and what to retrieve based on the LLM’s information needs during the text generation process.We evaluate DRAGIN …

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Dec 5, 2024 · The DRAGIN framework allows us to look to move a few steps ahead of the traditional RAG framework. It allows us to perform multiple retrievals, based on the information needs of …

Dec 5, 2024 · The DRAGIN framework allows us to look to move a few steps ahead of the traditional RAG framework. It allows us to perform multiple retrievals, based on the information needs of …

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We comprehensively evaluate DRAGIN along with existing dynamic RAG frameworks over four knowledge-intensive generation benchmarks. Experimental results show that DRAGIN achieves …