recurrent-looped-tranformer

Recurrent Looped Transformer (RLT) is a neural network architecture that integrates recurrent mechanisms with transformer-based processing. The project presents research into hybrid approaches that maintain transformer computational advantages while incorporating feedback loops for sequential data handling.

Accessible via the official project page, RLT represents work in advancing transformer architectures for improved sequence modeling. The implementation explores the intersection of recurrent and transformer-based neural networks.