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Description
RAGRouter-Bench is a dataset and benchmark designed for adaptive Retrieval-Augmented Generation routing. It contains 7,727 queries and 21,460 documents across four domains: Wikipedia, Literature, Legal, and Medical. The dataset was created by Chaplain0908 and last updated on January 23, 2026.
Use Cases
Benchmarking RAG system performance based on the described multi-domain query-document corpus.
Evaluating query-corpus compatibility for routing decisions based on the three query types: Factual, Reasoning, and Summary.
Training adaptive retrieval models based on the dataset's structured queries and documents.
Comparing retrieval strategies across the four specified domains: Wikipedia, Literature, Legal, and Medical.
Strengths
Contains 7,727 queries and 21,460 documents, providing substantial material for evaluation.
Covers four distinct domains, likely offering diverse linguistic and structural contexts.
Includes three specific query types, which may allow for nuanced performance analysis.
Limitations
Column-level documentation is absent; field semantics must be inferred after download.
Row count is unknown, which may limit suitability assessment for large-scale training.
Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
Source
Chaplain0908 on Hugging Face.
Collection Method
Constructed from existing datasets: MuSiQue, QuALITY, UltraDomain, and GraphRAGBench.
Time Range
null
Freshness
Last updated 2026-01 23 07:37:45; freshness should be verified.
Geography
null
License is unknown; terms of use must be verified before application.