Papers with Source Planning Optimisation method

1 papers
Towards Omni-RAG: Comprehensive Retrieval-Augmented Generation for Large Language Models in Medical Applications (2025.acl-long)

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Challenge: Existing approaches to source planning fail to achieve this due to misalignment between the model’s expectation of the sources and their actual content.
Approach: They propose a method to optimise large-scale medical knowledge models by combining multiple medical knowledge sources into one query.
Outcome: The proposed method significantly improves multi-source planning performance while training a smaller model to learn source alignment.

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