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1. 2026PreprintCurated

   BM25 Wins at Scale: A Scaling Study of Retrieval-Augmented Generation Paradigms

   Wang et al.

   A controlled scaling study of retrieval-augmented generation paradigms, usually evaluated on different benchmarks at one corpus size. Corpus size is varied along 28 strictly nested tiers spanning roughly 450-fold while questions and a fixed bedrock of relevant and adversarial documents are held constant, under one reader model and one judging protocol. The result is a scale-dependent crossover rather than an unconditional winner. File-System Agent leads at the smallest shared tiers but costs 39 times more query tokens at the bedrock and becomes less effective as the search space grows. Around 10 million corpus tokens BM25 overtakes it and leads at every larger shared tier, with a margin approaching 20 points at full scale, and anchors the low-cost end of the Pareto frontier without any LLM-based construction. Dense retrieval remains efficient but less accurate; graph-based RAG encounters construction walls before deployment scale and its scalable variants stay below BM25 at shared tiers. The authors conclude that corpus growth increasingly favours global candidate ranking, with agentic reasoning working best after ranked discovery rather than in place of it.

   Retrieval & RAGEvaluation

   arXiv

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