arXiv cs.CLPaper
Knowledge Acquisition During Pre-training? Large Language Models Learn Better With Auxiliary Views
This is a pre-training insight that applies to model builders and scaling studies, not to people using existing models. If you're training your own LLM, this suggests that data diversity and reformulation matter more than raw repetition, which could improve your training efficiency. For API users, this is future context but not actionable today.