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Inefficient Deduplication in LLM Pretraining

The article highlights the underestimated importance of deduplication in Large Language Model (LLM) pretraining, suggesting that inefficient deduplication can have significant costs. This process is crucial for building LLMs, particularly for specific languages like Indic languages. The challenge lies in effectively implementing deduplication to ensure efficient and effective model training.

Computing & Technology, Computer Science, Machine Learning