10 citations · 15 across the 5 of their papers we have counts for
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cs.IR2025★ 5 cited
Retrieval-Augmented Generation in Industry: An Interview Study on Use Cases, Requirements, Challenges, and Evaluation
Lorenz Brehme, Benedikt Dornauer, Thomas Ströhle +2
Retrieval-Augmented Generation (RAG) is a well-established and rapidly evolving field within AI that enhances the outputs of large language models by integrating relevant informati…
cs.IR2025★ 10 cited
Can LLMs Be Trusted for Evaluating RAG Systems? A Survey of Methods and Datasets
Lorenz Brehme, Thomas Ströhle, Ruth Breu
Retrieval-Augmented Generation (RAG) has advanced significantly in recent years. The complexity of RAG systems, which involve multiple components-such as indexing, retrieval, and g…