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.