Methods › Computer Vision › Backbone Architectures › FFF

Fast Feedforward Networks

FFF

6 papers tagged archive 2025-07-28

Introduced by Peter Belcak et al. in Fast Feedforward Networks

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

A log-time alternative to feedforward layers outperforming both the vanilla feedforward and mixture-of-experts approaches.

PaperSource

Papers archive 2025-07-28

6 shown of 6, 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

8 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
Mixture-of-Experts2
ARC1
Benchmarking1
CPU1
Computational Efficiency1
Denoising1
Image Stylization1
Language Modelling1

Usage over time archive 2025-07-28

Papers per year tagged with FFF: 2023 to 2024, peak 4 4 0 2023: 2 papers 2023 2024: 4 papers 2024
Papers per year the archive tags with this method, by the paper's archive date (6 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

Backbone Architectures

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