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M. Granitzer

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Preprint Aug 2026

When Is Complex Chunking Worth It? A Multi-Objective Evaluation of Chunking Methods at Scale

This work evaluates eight representative chunking strategies across two scalable corpora, three embedding models, and multiple corpus sizes, measuring both retrieval effectiveness and system-level costs and shows that computationally expensive methods rarely provide consistent gains over simpler chunking.

Laura Caspari, K. G. Dastidar, M. Dinzinger et al. · 0 citations

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