GitHub Typo Corpus: A Large-Scale Multilingual Dataset of Misspellings and Grammatical Errors

28 November 2019

Papers citing "GitHub Typo Corpus: A Large-Scale Multilingual Dataset of Misspellings and Grammatical Errors"

8 / 8 papers shown

Title
A Methodology for Generative Spelling Correction via Natural Spelling Errors Emulation across Multiple Domains and Languages Nikita Martynov Mark Baushenko Anastasia Kozlova Katerina Kolomeytseva Aleksandr Abramov Alena Fenogenova 30 2 0 18 Aug 2023
Domain specificity and data efficiency in typo tolerant spell checkers: the case of search in online marketplaces Dayanand Ubrangala Juhi Sharma R. Kondapalli Kiran Rama Amit Agarwala Laurent Boué 8 0 0 03 Aug 2023
Make Text Unlearnable: Exploiting Effective Patterns to Protect Personal Data Xinzhe Li Ming Liu Shang Gao MU 25 8 0 02 Jul 2023
READIN: A Chinese Multi-Task Benchmark with Realistic and Diverse Input Noises Chenglei Si Zhengyan Zhang Yingfa Chen Xiaozhi Wang Zhiyuan Liu Maosong Sun AAML 22 1 0 14 Feb 2023
Correcting diacritics and typos with a ByT5 transformer model Lukas Stankevicius M. Lukoševičius J. Kapočiūtė-Dzikienė Monika Briediene Tomas Krilavičius 11 20 0 31 Jan 2022
VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning Qibin Chen Jeremy Lacomis Edward J. Schwartz Graham Neubig Bogdan Vasilescu Claire Le Goues VLM 16 33 0 05 Dec 2021
Do We Need Online NLU Tools? Petr Lorenc Petro Marek Jan Pichl Jakub Konrád Jan Sedivý 13 6 0 19 Nov 2020
Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task Marcin Junczys-Dowmunt Roman Grundkiewicz Shubha Guha Kenneth Heafield 33 192 0 16 Apr 2018