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Hajar Emami Gohari

1 accepted papers

2026

GneissWeb: Preparing High Quality Data for LLMs at Scale

ICLR 2026poster

Data quantity and quality play a vital role in determining the performance of Large Language Models (LLMs). High-quality data, in particular, can significantly boost the LLM's ability to generalize on a wide range of downstream tasks. In this paper, we introduce **GneissWeb**, a large dataset of aro…

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