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RefinedWeb: scaled filtering and deduplication for web-only pretraining

Contribution grade

Language-model data curation · Human-designed research method or resource

Reference score115,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Combined text extraction, document/line filtering and exact/fuzzy deduplication at web scale, releasing a600B-token extract and studying web-only language-model pretraining against curated-corpus baselines.

Scientific scope

Combined text extraction, document/line filtering and exact/fuzzy deduplication at web scale, releasing a600B-token extract and studying web-only language-model pretraining against curated-corpus baselines. Five-trillion-token internal corpus differs from released600B-token extract. Controlled reported model comparisons do not prove curated non-web data is never useful or all downstream tasks improve. Distinct from Falcon model architecture; inherited extraction/MinHash methods retain credit.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Five-trillion-token internal corpus differs from released600B-token extract. Controlled reported model comparisons do not prove curated non-web data is never useful or all downstream tasks improve. Distinct from Falcon model architecture; inherited extraction/MinHash methods retain credit.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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