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Editorial:Special Section on Challenges and Opportunities in Retrieval-Augmented Generation for LLMs:Techniques,Trends,and Applications
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作者 Philip S.Yu Haofen Wang Feida Zhu 《Big Data Mining and Analytics》 2026年第2期339-340,共2页
Models(LLMs)by integrating external knowledge to substantially improve accuracy and mitigate hallucinations.As a pivotal technology in the contemporary generative Artificial Intelligence(AI)landscape,RAG addresses fun... Models(LLMs)by integrating external knowledge to substantially improve accuracy and mitigate hallucinations.As a pivotal technology in the contemporary generative Artificial Intelligence(AI)landscape,RAG addresses fundamental challenges in knowledge-intensive tasks.This special issue serves as a dedicated platform to showcase these cutting-edge advancements.It features six rigorously peer-reviewed papers that present state-of-the-art research and applications in the rapidly evolving field of RAG. 展开更多
关键词 llms external knowledge integrating external knowledge accuracy knowledge intensive tasks artificial intelligence retrieval augmented generation generative artificial intelligence ai landscaperag
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