File:Recurrent Memoty Transformer.png

English: RMT enhances the Transformer model by introducing global memory tokens, facilitating segment-level recurrence. It integrates unique read and write memory tokens into the input sequence, enabling the use of multiple memory tokens in each read/write block. Notably, the updated write memory representations are seamlessly passed to the subsequent segment, ensuring a dynamic and context-rich sequence processing. It leverages the ability of transformers to capture complex patterns within data, while also utilizing the sequential processing capabilities of recurrent networks. This allows the RMT to effectively handle tasks with long-term dependencies and complex sequential dynamics.