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20242026
most citedMATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models

2 citations · 2 across the 6 of their papers we have counts for

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cs.LG2026

ÜberWeb: Insights from Multilingual Curation for a 20-Trillion-Token Dataset

DatologyAI, :, Aldo Gael Carranza +32

Multilinguality is a core capability for modern foundation models, yet training high-quality multilingual models remains challenging due to uneven data availability across language…

cs.LG2026

DatBench: Discriminative, Faithful, and Efficient VLM Evaluations

DatologyAI, :, Siddharth Joshi +30

Empirical evaluation serves as the primary compass guiding research progress in foundation models. Despite a large body of work focused on training frontier vision-language models…