arXiv:2605. 26476v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become critical for knowledge-intensive applications, yet evaluating its performance in vertical domains remains difficult due to domain complexity, diverse context scales, and heavy reliance on expert assessments that are costly, inconsistent, and non-scalable.
Paper
FAB-Bench: A Framework for Adaptive RAG Benchmarking in Semiconductor Manufacturing
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