Methods › Natural Language Processing › Transformers › PAR Transformer
PAR Transformer
Introduced by Swetha Mandava et al. in Pay Attention when Required
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
PAR Transformer is a Transformer model that uses 63% fewer self-attention blocks, replacing them with feed-forward blocks, while retaining test accuracies. It is based on the Transformer-XL architecture and uses neural architecture search to find an an efficient pattern of blocks in the transformer architecture.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Pay Attention when Required 9 Sep 2020 · 2 repositories · arXiv:2009.04534
Tasks archive 2025-07-28
4 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections