mtala3t / GEC-Info

Repository to collect and categorize Grammatical Error Correction papers.

GEC Information

Something information of grammatical error correction :)
Information will be added sometimes.

It can also be viewed on GitHub Pages

Overview

• Surveys
• Shared Tasks
• Datasets
  • For Training
  • For Evaluation
• Performance Measures
  • Reference-based
  • Reference-less
• Quality Estimation
• Models / Architectues
  • Supervised
  • Unsupervised
• Strategies
• Data Augmentation
• Analyses / Findings
• Other Tools
• Spoken Domain
• Applications
• Projects
• Other Materials
• Related Tasks
  • Grammatical Error Detection
  • Feedback Comment Generation
• Other Languages
  • Arabic
  • Bangla
  • Chinese
  • Czech
  • Geek
  • German
  • Hindi
  • Japanese
  • Lithuanian
  • Romain
  • Russian
  • Spanish
  • Ukrainian

Surveys

Title	Year	Page	Note
"A Comprehensive Survey of Grammar Error Correction"	2020	[paper]

Shared Tasks

Name	Year	Paper	Note
HOO 2011	2011	[paper]	[website]
HOO 2012	2012	[paper]	[website]
CoNLL-2013	2013	[paper]	[website]
CoNLL-2014	2014	[paper]	[website] [system outputs]
BEA-2019	2019	[paper]	[website] [system outpus]

Datasets

For Training (Real Data)

Name	Year	Paper	Note
EFCamDat	2014	[Automatic Linguistic Annotation ofLarge Scale L2 Databases: The EF-Cambridge Open Language Database(EFCamDat)] [The EF Cambridge Open Language Database (efcamdat) Information for Users]	[download v2]
GitHub Typo Corpus	2019	[GitHub Typo Corpus: A Large-Scale Multilingual Dataset of Misspellings and Grammatical Errors]	[download]
W&I+LOCNESS on BEA2019 Shared Task	2019	[Developing an Automated Writing Placement System for ESL Learners ]	[direct download]
FCE	2011	[A New Dataset and Method for Automatically Grading ESOL Texts]	[direct download]
NUCLE	2013	[Building a Large Annotated Corpus of Learner English: The NUS Corpus of Learner English]	[download]
ICNALE	2013	[The ICNALE and Sophisticated Contrastive Interlanguage Analysis of Asian Learners of English]	[download]
Lang-8	2011	[Mining Revision Log of Language Learning SNS for Automated Japanese Error Correction of Second Language Learners]	[website] [download: Fill this form] Related tools are useful. See the [Other Tools] for the details.

For Training (Pseudo/Systhetic Data)

Name	Year	Paper	Note
PIE-synthetic	2019	[Parallel Iterative Edit Models for Local Sequence Transduction]	[download]

For Evaluation

Name	Year	Paper	Note
KJ	2011	[Creating a manually error-tagged and shallow-parsed learner corpus]	[download]
CoNLL-2013	2013	[The CoNLL-2013 Shared Task on Grammatical Error Correction]	[direct download]
CoNLL-2014	2014	[The CoNLL-2014 Shared Task on Grammatical Error Correction]	[direct download]
10 additional annotations for the CoNLL14	2015	[How Far are We from Fully Automatic High Quality Grammatical Error Correction?]	[direct download]
8 additional annotations for the CoNLL14	2016	[Reassessing the Goals of Grammatical Error Correction: Fluency Instead of Grammaticality]	[download]
JFLEG	2017	[JFLEG: A Fluency Corpus and Benchmark for Grammatical Error Correction]	[download]
GMEG-Data	2019	[Enabling Robust Grammatical Error Correction in New Domains: Data Sets, Metrics, and Analyses]	[code]
CWEB	2020	[Grammatical Error Correction in Low Error Density Domains: A New Benchmark and Analyses]	[download]
ErAConD	2021	[ErAConD : Error Annotated Conversational Dialog Dataset for Grammatical Error Correction]	[data] Training dataset is included.

Performance measures

Reference-based

Name	Year	Paper	Note
M^2 Scorer	2012	[Better Evaluation for Grammatical Error Correction]	[code] It is often used to evaluate CoNLL-2013 and CoNLL-2014.
GLEU	2015	[Ground Truth for Grammatical Error Correction Metrics] [GLEU Without Tuning]	[code] It is often used to evaluate JFLEG.
I-measure	2015	[Towards a standard evaluation method for grammatical error detection and correction]	[code] Code is available only python 2.x.
ERRANT	2016	[Automatic Extraction of Learner Errors in ESL Sentences Using Linguistically Enhanced Alignments] [Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction]	[code] It is often used to evaluate BEA-2019.
GMEG-Metric	2019	[Enabling Robust Grammatical Error Correction in New Domains: Data Sets, Metrics, and Analyses]	[code] Ridge regression using existing metrics (e.g. ERRANT, GLEU) as features.
GoToScorer	2019	[Taking the Correction Difficulty into Account in Grammatical Error Correction Evaluation]	[code] It can be evaluated systems considering error correction difficulty.

Reference-less

Keywords / Overview	Year	Paper	Note
Scoring by counting the errors	2016	[There’s No Comparison: Reference-less Evaluation Metrics in Grammatical Error Correction]	[code]
Fluency + grammaticality + meaning preservation	2017	[Reference-based Metrics can be Replaced with Reference-less Metrics in Evaluating Grammatical Error Correction Systems]
USim	2018	[Reference-less Measure of Faithfulness for Grammatical Error Correction]	[code]
SOME	2020	[SOME: Reference-less Sub-Metrics Optimized for Manual Evaluations of Grammatical Error Correction]	[code]
Scribendi Score	2021	[Is this the end of the gold standard? A straightforward reference-less grammatical error correction metric]	[Unofficial code]

Quality Estimation

Keywords / Overview	Year	Paper	Note
	2022	Proficiency Matters Quality Estimation in Grammatical Error Correction

Models / Architectures

Supervised

Keywords / Overview	Year	Paper	Note
Phrase-based SMT	2016	[Phrase-based Machine Translation is State-of-the-Art for Automatic Grammatical Error Correction]	[code]
Neural reinforcement learning	2017	[Grammatical Error Correction with Neural Reinforcement Learning]
Word-level SMT enhanced NNJMs + char-based SMT	2017	[Connecting the Dots: Towards Human-Level Grammatical Error Correction]	[code]
First NMT-based approach	2016	[Grammatical error correction using neural machine translation]
SMEG	2017	[Systematically Adapting Machine Translation for Grammatical Error Correction]	[code]
A nested attention (word and char attention)	2017	[A Nested Attention Neural Hybrid Model for Grammatical Error Correction]
Re-ranking N-best sentence (by SMT) with LSTM-based GED	2017	[Neural Sequence-Labelling Models for Grammatical Error Correction]
CNN-based Encder-Decoder approach	2018	[A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction]	[code]
Fluency boosting learning	2018	[Fluency Boost Learning and Inference for Neural Grammatical Error Correction]	[code] ACL2018
Fluency boosting learning (added round-way error correction)	2018	[Reaching Human-level Performance in Automatic Grammatical Error Correction: An Empirical Study]	[code] Microsoft Research Technical Report
Hybrid SMT and NMT	2018	[Near Human-Level Performance in Grammatical Error Correction with Hybrid Machine Translation]
Copy-Augmented Architecture	2019	[Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data]	[code]
Consider a few previous sentences	2019	[Cross-Sentence Grammatical Error Correction]	[code]
PIE	2019	[Parallel Iterative Edit Models for Local Sequence Transduction]	[code]
LaserTagger	2019	[Encode, Tag, Realize: High-Precision Text Editing]	[code]
Pretrain by DAE + sequential transfer learning	2019	[A Neural Grammatical Error Correction System Built On Better Pre-training and Sequential Transfer Learning]	[code] BEA-2019: Kakao&Brain
Use sentence-level error dectection	2019	[The AIP-Tohoku System at the BEA-2019 Shared Task]	BEA-2019: AIP-Tohoku
Four CNN + eight Transformer	2019	[The LAIX Systems in the BEA-2019 GEC Shared Task]	BEA-2019: LAIX
Combine Transformer+CNN with FST + Re-ranking	2019	[Neural and FST-based approaches to grammatical error correction]	BEA-2019: CAMB-CLED
Transformer seq2seq + BERT re-ranker	2019	[TMU Transformer System Using BERT for Re-ranking at BEA 2019 Grammatical Error Correction on Restricted Track]	BEA-2019: TMU
Apply noisy channel with BERT and GPT-2 as LM	2019	[Noisy Channel for Low Resource Grammatical Error Correction]	BEA-2019: Siteimprove
Use Finite State Transducers	2019	[Neural Grammatical Error Correction with Finite State Transducers]
GECToR	2020	[GECToR – Grammatical Error Correction: Tag, Not Rewrite]	[code]
BERT-fuse	2020	[Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction]	[code]
Adversarial approach (G:seq2seq D:sentence-pair classification)	2020	[Adversarial Grammatical Error Correction]
Erroneous span correction and detection	2020	[Improving the Efficiency of Grammatical Error Correction with Erroneous Span Detection and Correction]
Document-level approach	2020	[Document-level grammatical error correction]	[code]
Seq2Edits	2020	[Seq2Edits: Sequence Transduction Using Span-level Edit Operations]	[code]
Beam search considering copy probability	2020	[Generating Diverse Corrections with Local Beam Search for Grammatical Error Correction]
BART-based	2020	[Stronger Baselines for Grammatical Error Correction Using a Pretrained Encoder-Decoder Model]	[code]
VERNet	2021	[Neural Quality Estimation with Multiple Hypotheses for Grammatical Error Correction]	[code]
Shallow Aggressive Decoding	2021	[Instantaneous Grammatical Error Correction with Shallow Aggressive Decoding]	[code]
T5-based	2021	[A Simple Recipe for Multilingual Grammatical Error Correction]	[code]
GAN-like sequence labeling	2021	[Grammatical Error Correction as GAN-like Sequence Labeling]
Diversity-Driven Combination (DDC)	2021	[Diversity-Driven Combination for Grammatical Error Correction]	[code]
Select a system for each error type with IP	2021	[System Combination for Grammatical Error Correction Based on Integer Programming]	[code]
Use multiclass GED for Transformer seq2seq and reranking	2021	[Multi-Class Grammatical Error Detection for Correction: A Tale of Two Systems]
GEC for writing improvement model adapted to the writer’s L1	2021	[Beyond Grammatical Error Correction: Improving L1-influenced research writing in English using pre-trained encoder-decoder models]	[code]
Constrastive Leaning approach	2021	[Grammatical Error Correction with Contrastive Learning in Low Error Density Domains]	[code]
Sequence Span Rewriting	2021	[Improving Sequence-to-Sequence Pre-training via Sequence Span Rewriting]
Dependent Self-Attention (DSA)	2021	[Grammatical Error Correction with Dependency Distance]
	2022	Interpretability for Language Learners Using Example-Based Grammatical Error Correction	[code]
	2022	Type-Driven Multi-Turn Corrections for Grammatical Error Correction	[code]
GECToR Large	2022	Ensembling and Knowledge Distilling of Large Sequence Taggers for Grammatical Error Correction	[code] [Author's Master Thesis]

Unsupervised

Keywords / Overview	Year	Paper	Note
5-gram LM based approach	2018	[Language Model Based Grammatical Error Correction without Annotated Training Data]	[code]
Train GRU models for each of five error types	2018	[A Simple but Effective Classification Model for Grammatical Error Correction]
Use Finite State Transducers	2019	[Neural Grammatical Error Correction with Finite State Transducers]
LSTM tagger for word coice task	2019	[Choosing the Right Word: Using Bidirectional LSTM Tagger for Writing Support Systems]	[code]
Use LM (BERT, GPT-1,2)	2019	[The Unreasonable Effectiveness of Transformer Language Models in Grammatical Error Correction]
Create erroneous data from monolingual data	2019	[Minimally-Augmented Grammatical Error Correction]	Supervised setting is also performed
LM-Critic	2021	[LM-Critic: Language Models for Unsupervised Grammatical Error Correction]	[code] Supervised setting is also performed

Strategies

Keywords / Overview	Year	Paper	Note
Some methods that can be adapted neural MT	2018	[Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task]	[code]
Iterative decoding	2018	[Weakly Supervised Grammatical Error Correction using Iterative Decoding]
Combine systems automatically	2019	[Learning to combine Grammatical Error Corrections]	[code]
Add adversarial examples continually	2020	[Improving Grammatical Error Correction Models with Purpose-Built Adversarial Examples]
Cross-lingual Transfer Learning	2020	[Cross-lingual Transfer Learning for Grammatical Error Correction]
Data Weighted Training Strategies	2020	[Data Weighted Training Strategies for Grammatical Error Correction]

Data Augmentation

Keywords / Overview	Year	Paper	Note
Make artificial errors in a probabilistic manner	2014	[Generating artificial errors for grammatical error correction]
Back translation	2016	[Improving Neural Machine Translation Models with Monolingual Data]
SMT based MT + pattern extraction	2017	[Artificial Error Generation with Machine Translation and Syntactic Patterns]
Diverse back translation with noisy beam search	2018	[Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction]
DirectNoise	2019	[Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data]	The method was first called "DirectNoise" by [kiyono+ 2019]?
Substituting words using confusion sets	2019	[Neural Grammatical Error Correction Systems with Unsupervised Pre-training on Synthetic Data]	[synthetic data] BEA-2019: UEDIN-MS
Error+Context Dictionary	2019	[Improving Precision of Grammatical Error Correction with a Cheat Sheet]	BEA-2019: Buffalo
Use Google Translate for making pseudo data	2019	[(Almost) Unsupervised Grammatical Error Correction using a Synthetic Comparable Corpus]	BEA-2019: TMU in Low Resource
Inverted Spellchecker + Patterns+POS	2019	[A Comparative Study of Synthetic Data Generation Methods for Grammatical Error Correction]
Methods for erroneous data generation	2019	[Erroneous data generation for Grammatical Error Correction]	BEA-2019: Shuyao
Wikipedia revision & Wikipedia round-trip translation	2019	[Corpora Generation for Grammatical Error Correction]
Create confusion sets by edit distance, word embeddings, spell-breaking	2019	[Minimally-Augmented Grammatical Error Correction]	Supervised setting is also performed
Explore methods to make pseude data, seed corpus, training settings	2019	[An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction]	[code]
	2020	[Massive Exploration of Pseudo Data for Grammatical Error Correction]
Control error rates and error types by rule-based corruption and filtered back-translation	2020	[Controllable Data Synthesis Method for Grammatical Error Correction]
Use machine translation pairs	2020	[Improving Grammatical Error Correction with Machine Translation Pairs]
Edit latent representation	2020	[Improving Grammatical Error Correction with Data Augmentation by Editing Latent Representation]
Consider learner’s error tendency	2020	[Grammatical Error Correction Using Pseudo Learner Corpus Considering Learner’s Error Tendency]
Tagged corruption	2021	[Synthetic Data Generation for Grammatical Error Correction with Tagged Corruption Models]	[code]
Use 188 modules	2021	[Various Errors Improve Neural Grammatical Error Correction]	[code]
Use real error petterns and linguistic knowledge	2021	[Data Augmentation of Incorporating Real Error Patterns and Linguistic Knowledge for Grammatical Error Correction]
Divide non-English sentence into chunks → translate to English for each of them → concatenate	2021	[Grammatical Error Generation Based on Translated Fragments]

Data Cleaning

Keywords / Overview	Year	Paper	Note
A Self-Refinement Strategy for Noise Reduction	2020	[A Self-Refinement Strategy for Noise Reduction in Grammatical Error Correction]
cLang8 (Cleaned Lang-8)	2021	[A Simple Recipe for Multilingual Grammatical Error Correction]	[code]

Analyses / Findings

Keywords / Overview	Year	Paper	Note
Re-rank the CoNLL14 systems by human evaluation	2015	[Human Evaluation of Grammatical Error Correction Systems]	[code]
	2015	[How Far are We from Fully Automatic High Quality Grammatical Error Correction?]
Human annotation focused on fluency	2016	[Reassessing the Goals of Grammatical Error Correction: Fluency Instead of Grammaticality]	[code]
	2017	[GEC into the future: Where are we going and how do we get there?]
MEAGE	2018	[Automatic Metric Validation for Grammatical Error Correction]	[code]
	2018	[Inherent Biases in Reference-based Evaluation for Grammatical Error Correction]	[code]
	2018	[Assessing Grammatical Correctness in Language Learning]
Reassess M^2, I-measure, GLEU by comparing human evaluation	2018	[A Reassessment of Reference-Based Grammatical Error Correction Metrics]	[code]
Quality estimation (and re-ranking using estimated score)	2018	[Neural Quality Estimation of Grammatical Error Correction]	[code]
Evaluate four systems (SMT, CNN, LSTM, Transformer) for six corpora (CoNLL13&14, FCE, JFLEG, KJ, ICNALE)	2019	[Cross-Corpora Evaluation and Analysis of Grammatical Error Correction Models — Is Single-Corpus Evaluation Enough?]
Compare CNN, Transformer, PRPN, ON-LSTM as back-translation models	2019	[The Unbearable Weight of Generating Artificial Errors for Grammatical Error Correction]
GEC for post-processing	2021	Automatic Grammatical Error Correction for Sequence-to-sequence Text Generation: An Empirical Study
CGOP	2020	[Comparison of the Evaluation Metrics for Neural Grammatical Error Correction With Overcorrection]	Metric Considering overcorrection
Create new gold data by post-editing system outputs	2021	[How Good (really) are Grammatical Error Correction Systems?]
Explore whether models have grammatical knowledge with Known-setting and Unknown-setting	2021	[Do Grammatical Error Correction Models Realize Grammatical Generalization?]
Compare CNN, LSTM, transformer or combinations of them as BT models	2021	[Comparison of Grammatical Error Correction Using Back-Translation Models]
	2022	Uncertainty Determines the Adequacy of the Mode and the Tractability of Decoding in Sequence-to-Sequence Models

Spoken Domain

Keywords / Overview	Year	Paper	Note
Detection	2019	AUTOMATIC GRAMMATICAL ERROR DETECTION OF NON-NATIVE SPOKEN LEARNER ENGLISH
Detection	2020	Grammatical error detection in transcriptions of spoken English
Correction, disfluency detection model	2020	Spoken Language ‘Grammatical Error Correction’

Applications

Name	Year	Paper	Note
GECko++		[GECko+: a Grammatical and Discourse Error Correction Tool]	[website] [code] An English assiting tool. Correction grammatical error and re-ordering sentences automatically.
MiSS	2021	[MiSS: An Assistant for Multi-Style Simultaneous Translation]	[website] [demo video]

Projects

Name	Website
GramFormer	[GitHub]

Other Tools

Name	Code	Note
Lang8-NAIST-extractor	[code]	Scripts for extracting error-correct pairs from the Lang-8 Corpus.
M2Converter	[code]	Scripts for converting m2 file into source file and target file.
EFCamDat-Preprocess	[code]

Other materials

Name	Paper	Note
NLP-progress		[website] The performance ranking on some datasets.
A Crash Course in Automatic Grammatical Error Correction	[paper]	[materials] The tutorial about GEC in COLING2020.
Chunngai/gec-papers		[github] The papers are being compiled around 2019-2020?

Related Tasks

Grammatical Error Detection

Keywords / Overview	Year	Paper	Note
A weighted measure according to crowdsourcing results (for GED)	2011	[They Can Help: Using Crowdsourcing to Improve the Evaluation of Grammatical Error Detection Systems]
	2018	[Wronging a Right: Generating Better Errors to Improve Grammatical Error Detection]	[code]
Bi-LSTM with contextual word embeddings	2019	[Context is Key: Grammatical Error Detection with Contextual Word Representations]
Multi-head and multi-layer attention	2019	[Multi-Head Multi-Layer Attention to Deep Language Representations for Grammatical Error Detection]
	2021	[Exploring the Capacity of a Large-scale Masked Language Model to Recognize Grammatical Errors]

Feedback Comment Generation

Keywords / Overview	Year	Paper	Note
	2014	[Correcting Preposition Errors in Learner English Using Error Case Frames and Feedback Messages]
English grammar checker with feedback in Japanese	2018	[Grammatical Error Checker for Japanese Learners of English]	This is not a research as a feedback comment generation, but I classify it here for now
	2019	[Toward a Task of Feedback Comment Generation for Writing Learning]
	2020	[Creating Corpora for Research in Feedback Comment Generation]
	2021	[Shared Task on Feedback Comment Generation for Language Learners]

Other Languages

Arabic

Keywords / Overview	Year	Paper	Note
Arabic Learner Corpus	2013	[Arabic Learner Corpus v1: A New Resource for Arabic Language Research]	[website]
QALB	2014	[Large Scale Arabic Error Annotation: Guidelines and Framework]	[QALB Project Website]
QALB 2014 Shared Task	2014	[The First QALB Shared Task on Automatic Text Correction for Arabic]	[website]
QALB 2015 Shared Task	2015	[The Second QALB Shared Task on Automatic Text Correction for Arabic]
ARETA	2021	[Automatic Error Type Annotation for Arabic]	[code]

Bangla

Keywords / Overview	Year	Paper	Note
	2021	[Development of Bangla Spell and Grammar Checkers: Resource Creation and Evaluation]

Chinese

Keywords / Overview	Year	Paper	Note
NLPCC-2018 Shared Task	2018	[Overview of the NLPCC 2018 Shared Task: Grammatical Error Correction]	[data]
Two-stage: Spell checker → seq2seq	2019	[A Two-Stage Model for Chinese Grammatical Error Correction]
CNN-based seq2seq	2019	[Chinese Grammatical Error Correction Based on Convolutional Sequence to Sequence Model]
MaskGEC	2020	[MaskGEC: Improving Neural Grammatical Error Correction via Dynamic Masking]
	2020	[Chinese Grammatical Error Detection Based on BERT Model]
	2020	[BERT Enhanced Neural Machine Translation and Sequence Tagging Model for Chinese Grammatical Error Diagnosis]
	2020	[Heterogeneous Recycle Generation for Chinese Grammatical Error Correction]
NLPTEA-2020 Shared Task	2020	[Overview of NLPTEA-2020 Shared Task for Chinese Grammatical Error Diagnosis]
Tail-to-Tail Non-Autoregressive Sequence Prediction	2021	[Tail-to-Tail Non-Autoregressive Sequence Prediction for Chinese Grammatical Error Correction]
	2021	"Is Whole Word Masking Always Better for Chinese BERT?": Probing on Chinese Grammatical Error Correction

Czech

Keywords / Overview	Year	Paper	Note
AKCES-GEC dataset	2019	[Grammatical Error Correction in Low-Resource Scenarios]	[data]
Grammar Error Correction Corpus for Czech (GECCC)	2022	Czech Grammar Error Correction with a Large and Diverse Corpus	[data]

Geek

Keywords / Overview	Year	Paper	Note
Greek Learner Corpus	2018	[Stand-off annotation in learner corpora: compiling the Greek Learner Corpus (GLC)]
ELERRANT	2021	[ELERRANT: Automatic Grammatical Error Type Classification for Greek]	[code]

German

Keywords / Overview	Year	Paper	Note
Falko-MERLIN dataset	2018	[Using Wikipedia Edits in Low Resource Grammatical Error Correction]	[data]

Hindi

Keywords / Overview	Year	Paper	Note
	2014	[Detection and correction of non word spelling errors in Hindi language]
HiWikiEd dataset	2020	[Generating Inflectional Errors for Grammatical Error Correction in Hindi]	[data]

Japanese

Keywords / Overview	Year	Paper	Note
Character-level RNN-based seq2seq	2018	[Automatic Error Correction on Japanese Functional Expressions Using Character-based Neural Machine Translation]
Constructing retrieval system for Japanese GEC	2019	[Grammatical-Error-Aware Incorrect Example Retrieval System for Learners of Japanese as a Second Language]
TMU Evaluation Corpus for Japanese Learners	2020	[Construction of an Evaluation Corpus for Grammatical Error Correction for Learners of Japanese as a Second Language]	[data: Fill this form]
Non-Autoregressive approach	2020	[Non-Autoregressive Grammatical Error Correction Toward a Writing Support System]
	2022	Construction of a Quality Estimation Dataset for Automatic Evaluation of Japanese Grammatical Error Correction

Lithuanian

Keywords / Overview	Year	Paper	Note
	2022	Towards Lithuanian grammatical error correction	[code]

Romain

Keywords / Overview	Year	Paper	Note
	2020	[Neural Grammatical Error Correction for Romanian]	[code]

Russian

Keywords / Overview	Year	Paper	Note
RULEC-GEC dataset	2019	[Grammar Error Correction in Morphologically Rich Languages: The Case of Russian]	[data]
RU-Lang8 dataset	2021	[New Dataset and Strong Baselines for the Grammatical Error Correction of Russian]	[data]

Spanish

Keywords / Overview	Year	Paper	Note
COWS-L2H	2020	[Developing NLP Tools with a New Corpus of Learner Spanish]	[data]

Ukrainian

Keywords / Overview	Year	Paper	Note
UA-GEC	2021	[UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian Language]	[data]