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Towards Scalable Data Diversification for Language Model Pretraining via Leverage Score Sampling
Data selection for language model pretraining faces a fundamental tension between quality and diversity. While quality filtering is empirically effective, it often induces diversity collapse: by favoring texts similar to high-quality reference corpora (e.g., educational or QA-style data), it systema
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