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Enhancing Generative AI with Retrieval-Augmented Generation: Techniques, Challenges and Applications
Abstract: Retrieval-Augmented Generation (RAG) is an augmentation of Large Language Models (LLMs) that uses external data sources during inference, which thus helps in eradicating no-table constraints ...
Abstract: To address the knowledge blind spots and hallucination issues of large language models (LLMs) in power grid cybersecurity, and to enhance their accuracy and practicality in decision support, ...
Retrieval-Augmented Generation (RAG) has emerged as an important means of enhancing the performance of large language models (LLMs) in knowledge-intensive tasks. However, most existing RAG strategies ...
fUniversité Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Centre for Research in Epidemiology and Statistics (CRESS), Paris, France gDepartment of Obstetrics and Reproductive Sciences, ...
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