This paper is well written. The results are pretty wild. They observed some amazing reduction in training resources required to achieve similar benchmarks to models trained on conventional data:

> We observe that even at the first checkpoint (10B tokens) of WRAP training, the average perplexity of the LLM on the Pile is lower than that achieved by pre-training on C4 for 15 checkpoints. This suggests a 15x pre-training speed-up.