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Methods › Natural Language Processing › Transformers › Performer

Performer

103 papers tagged archive 2025-07-28

Introduced by Krzysztof Choromanski et al. in Rethinking Attention with Performers

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Performer is a Transformer architecture which can estimate regular (softmax) full-rank-attention Transformers with provable accuracy, but using only linear (as opposed to quadratic) space and time complexity, without relying on any priors such as sparsity or low-rankness. Performers are linear architectures fully compatible with regular Transformers and with strong theoretical guarantees: unbiased or nearly-unbiased estimation of the attention matrix, uniform convergence and low estimation variance. To approximate softmax attention-kernels, Performers use a Fast Attention Via positive Orthogonal Random features approach (FAVOR+), leveraging new methods for approximating softmax and Gaussian kernels.

PaperSource

Papers archive 2025-07-28

30 shown of 103, 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.

Tasks archive 2025-07-28

20 shown of 149 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Language Modelling6
Decoder5
Time Series5
Classification4
Language Modeling4
Time Series Analysis4
Anomaly Detection3
Computational Efficiency3
Decision Making3
GPU3
Image Classification3
NeRF3
Novel View Synthesis3
Representation Learning3
Segmentation3
Sentiment Analysis3
image-classification3
Autonomous Driving2
Benchmarking2
Clustering2

Usage over time archive 2025-07-28

Papers per year tagged with Performer: 2020 to 2025, peak 25 25 0 2020: 3 papers 2020 2021: 17 papers 2021 2022: 24 papers 2022 2023: 23 papers 2023 2024: 25 papers 2024 2025: 11 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (103 dated). Bars are counts, not a trend claim.

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

Transformers

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