Papers with Performer-based model

1 papers
PermuteFormer: Efficient Relative Position Encoding for Long Sequences (2021.emnlp-main)

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Challenge: Existing Transformers that scale to long sequences are not compatible with relative position encoding.
Approach: They propose a Performer-based model with relative position encoding that scales linearly on long sequences.
Outcome: The proposed model outperforms performer on long sequences with no computational overhead and outperformed vanilla Transformer on most of the tasks.

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