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CANINE

6 papers tagged archive 2025-07-28

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

CANINE is a pre-trained encoder for language understanding that operates directly on character sequences—without explicit tokenization or vocabulary—and a pre-training strategy with soft inductive biases in place of hard token boundaries. To use its finer-grained input effectively and efficiently, Canine combines downsampling, which reduces the input sequence length, with a deep transformer stack, which encodes context.

Source: CANINE: Pre-training an Efficient Tokenization-Free...

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

6 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
Document Classification1
Inductive Bias1
Malware Classification1
Phishing Website Detection1
Sarcasm Detection1
Specificity1

Usage over time archive 2025-07-28

Papers per year tagged with CANINE: 2021 to 2025, peak 2 2 0 2021: 2 papers 2021 2022: 0 papers 2022 2023: 1 paper 2023 2024: 2 papers 2024 2025: 1 paper 2025
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

Language Models

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