Data Strategies for Large Language Models: A Unified Perspective on the Training Lifecycle
This work reviews data strategies across the training lifecycle and formulates them as policies that allocate a training budget over candidate examples, then divides methods by their decision granularity, model dependence, and temporal adaptivity, then compares their computational requirements and empirical support.
Yuan-Jian Xu, Jia-Ning Hao, Tian-Ze Sun et al.
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