arxiv.org/abs/2605.06546 introduces Token-Superposition Training (TST), a two-stage pretraining method from Nous Research. In the first stage, multiple input tokens are "superimposed" into a single embedding via averaging; in the second stage, the model is trained to "de-average" them, with the training time of a 10B MoE model compressed 2.5× and quality preserved.