Can an Agent Debug a Web Corpus? Agentic Auditing of Slovak FineWeb2

Marek Šuppa, Ivan Vykopal, Jaroslav Kopčan · 2026 · arXiv

DOI: 10.48550/arXiv.2610.31636 · open-access PDF

Abstract

Multilingual pipelines such as FineWeb2 apply one recipe across a thousand languages, leaving the failure modes of individual languages unanticipated. We use an LLM once, as a corpus debugger rather than a classifier: a tool-using agent explores the corpus through a read-only, budgeted API and compiles each finding into an executable test, which a native speaker then validates. On the 26.5M-document Slovak portion of FineWeb2, three runs costing \$2.21-\$2.84 each found seven findings over four phenomena. The largest is a machine-generated content farm of 1,408,437 documents (5.32%) that passe

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