• Corpus ID: 219966916

Memory Transformer

@article{Burtsev2020MemoryT,
  title={Memory Transformer},
  author={Mikhail S. Burtsev and Grigory V. Sapunov},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.11527}
}
Transformer-based models have achieved state-of-the-art results in many natural language processing (NLP) tasks. The self-attention architecture allows us to combine information from all elements of a sequence into context-aware representations. However, all-to-all attention severely hurts the scaling of the model to large sequences. Another limitation is that information about the context is stored in the same element-wise representations. This makes the processing of properties related to the… 

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