NVIDIA Introduces CLIMB: A Framework for Iterative Data Mixture Optimization in Language Model Pretraining

NVIDIA Introduces CLIMB: A Framework for Iterative Data Mixture Optimization in Language Model Pretraining

Challenges in Constructing Effective Pretraining Data Mixtures As large language models (LLMs) scale in size and capability, the choice of pretraining data remains a critical determinant of downstream performance. Most LLMs are trained on large, web-scale datasets such as Common Crawl, which provide broad coverage but lack explicit domain labels. This introduces difficulties in curating mixtures that balance general knowledge with domain-specifi…