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@article{li2024rag, title={RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data Rewards}, author={Li, Xinze and Mei, Sen and Liu, Zhenghao and Yan, Yukun and Wang, Shuo and Yu, ...
Abstract: This work presents a novel architecture for building Retrieval-Augmented Generation (RAG) systems to improve Question Answering (QA) tasks from a target corpus. Large Language Models (LLMs) ...
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