Joshua Nunley

FSN outperforms traditional transformer architectures in next-token prediction by leveraging frustrated synchronization, achieving lower validation loss even with fewer parameters.

Synchronizing self-attention on the torus reveals a new geometric framework that rivals traditional transformers in language modeling.