Beyond the Reranker: Do RAG Retrieval Enhancements Help Once a Strong Reranker Is Present?
Retrieval-augmented generation (RAG) is routinely extended with methods meant to improve retrieval: query expansion, hierarchical and cross-document summarization, graph-based expansion, per-query routing, rank fusion, and corrective re-retrieval. The benefits reported for these methods come almost exclusively from homogeneous corpora, predominantly Wikipedia prose. Whether they hold on the mixed-format collections common in practice, where code, markdown, tables, scientific PDFs, and prose are interleaved within one corpus, has not been measured. To study this directly, we build \textbf{HetDocQA}, a heterogeneous benchmark with \emph{chunker-agnostic} span-overlap relevance labels and co...
| Authors | Sadanand Singh, Allam Reddy, Manan Chopra |
|---|---|
| Primary category | cs.IR |
| Published | 14 June 2026 |
| Last updated at source | 14 June 2026 |
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