Methods › Natural Language Processing › Transformers › Charformer

Charformer

5 papers tagged archive 2025-07-28

Introduced by Yi Tay et al. in Charformer: Fast Character Transformers via Gradient-based Subword Tokenization

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

Charformer is a type of Transformer model that learns a subword tokenization end-to-end as part of the model. Specifically it uses GBST that automatically learns latent subword representations from characters in a data-driven fashion. Following GBST, the soft subword sequence is passed through Transformer layers.

Paper Source

Papers archive 2025-07-28

5 shown of 5, 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.

CharFormer: A Glyph Fusion based Attentive Framework for High-precision Character Image Denoising
16 Jul 2022 · 1 repository · arXiv:2207.07798
Patching Leaks in the Charformer for Efficient Character-Level Generation
27 May 2022 · 1 repository · arXiv:2205.14086
A New Generation of Perspective API: Efficient Multilingual Character-level Transformers
22 Feb 2022 · 0 repositories · arXiv:2202.11176
Patching Leaks in the Charformer for Generative Tasks
16 Jan 2022 · 0 repositories
Charformer: Fast Character Transformers via Gradient-based Subword Tokenization
23 Jun 2021 · 2 repositories · arXiv:2106.12672

Syntology ran 7 of 10 samples · 3 unverified

Tasks archive 2025-07-28

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

Task	Papers
Decoder	2
NMT	2
Denoising	1
Image Denoising	1
Inductive Bias	1
Linguistic Acceptability	1
Natural Language Inference	1
Paraphrase Identification	1
Semantic Textual Similarity	1
Sentiment Analysis	1
Toxic Comment Classification	1
Translation	1

Usage over time archive 2025-07-28

Papers per year the archive tags with this method, by the paper's archive date (5 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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