Grammatical Error Correction

Grammatical Error Correction (GEC) is the task of correcting different kinds of errors in text such as spelling, punctuation, grammatical, and word choice errors.

GEC is typically formulated as a sentence correction task. A GEC system takes a potentially erroneous sentence as input and is expected to transform it to its corrected version. See the example given below:

| Input (Erroneous) | Output (Corrected) | | ------------------------- | ---------------------- | |She see Tom is catched by policeman in park at last night. | She saw Tom caught by a policeman in the park last night.|

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 101–125 of 415 papers

Title	Date	Tasks	Status	Hype
Grammatical Error Correction: A Survey of the State of the Art	Nov 9, 2022	Grammatical Error CorrectionMachine Translation	—Unverified	0
From Spelling to Grammar: A New Framework for Chinese Grammatical Error Correction	Nov 3, 2022	Data AugmentationGrammatical Error Correction	—Unverified	0
Revisiting Grammatical Error Correction Evaluation and Beyond	Nov 3, 2022	Grammatical Error CorrectionMachine Translation	CodeCode Available	1
Towards standardizing Korean Grammatical Error Correction: Datasets and Annotation	Oct 25, 2022	AttributeDiversity	CodeCode Available	1
Focus Is What You Need For Chinese Grammatical Error Correction	Oct 23, 2022	Grammatical Error CorrectionSentence	—Unverified	0
SynGEC: Syntax-Enhanced Grammatical Error Correction with a Tailored GEC-Oriented Parser	Oct 22, 2022	Grammatical Error CorrectionSyntax Representation	CodeCode Available	1
FCGEC: Fine-Grained Corpus for Chinese Grammatical Error Correction	Oct 22, 2022	Grammatical Error CorrectionGrammatical Error Detection	CodeCode Available	1
Text Editing as Imitation Game	Oct 21, 2022	Action GenerationGrammatical Error Correction	CodeCode Available	0
Linguistic Rules-Based Corpus Generation for Native Chinese Grammatical Error Correction	Oct 19, 2022	Grammatical Error Correction	CodeCode Available	1
Multi-Perspective Document Revision	Oct 1, 2022	Grammatical Error CorrectionRelation Classification	—Unverified	0
Grammatical Error Correction: Are We There Yet?	Oct 1, 2022	Grammatical Error Correction	—Unverified	0
Position Offset Label Prediction for Grammatical Error Correction	Oct 1, 2022	Data AugmentationDecoder	—Unverified	0
IMPARA: Impact-Based Metric for GEC Using Parallel Data	Oct 1, 2022	Grammatical Error Correction	CodeCode Available	0
CCTC: A Cross-Sentence Chinese Text Correction Dataset for Native Speakers	Oct 1, 2022	Grammatical Error CorrectionSentence	CodeCode Available	2
Dynamic Negative Example Construction for Grammatical Error Correction using Contrastive Learning	Oct 1, 2022	Contrastive LearningGrammatical Error Correction	—Unverified	0
Judge a Sentence by Its Content to Generate Grammatical Errors	Aug 20, 2022	Grammatical Error CorrectionSentence	—Unverified	0
Gender Bias and Universal Substitution Adversarial Attacks on Grammatical Error Correction Systems for Automated Assessment	Aug 19, 2022	Adversarial AttackGrammatical Error Correction	—Unverified	0
Chinese grammatical error correction based on knowledge distillation	Jul 31, 2022	Grammatical Error CorrectionKnowledge Distillation	CodeCode Available	1
ErAConD: Error Annotated Conversational Dialog Dataset for Grammatical Error Correction	Jul 1, 2022	ChatbotGrammatical Error Correction	CodeCode Available	1
Frustratingly Easy System Combination for Grammatical Error Correction	Jul 1, 2022	Binary ClassificationGrammatical Error Correction	CodeCode Available	1
On Assessing and Developing Spoken ’Grammatical Error Correction’ Systems	Jul 1, 2022	Grammatical Error Correctionspeech-recognition	—Unverified	0
Mining Error Templates for Grammatical Error Correction	Jun 23, 2022	Grammatical Error CorrectionLanguage Modeling	CodeCode Available	2
Text Generation with Text-Editing Models	Jun 14, 2022	Grammatical Error CorrectionHallucination	—Unverified	0
ProQE: Proficiency-wise Quality Estimation dataset for Grammatical Error Correction	Jun 1, 2022	Grammatical Error Correction	—Unverified	0
Automatic Classification of Russian Learner Errors	Jun 1, 2022	ClassificationGrammatical Error Correction	—Unverified	0

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All datasets CoNLL-2014 Shared Task BEA-2019 (test)Falko-MERLIN JFLEG UA-GEC CoNLL-2014 Shared Task (10 annotations)Restricted Unrestricted _Restricted_EstGEC-L2 FCGEC MuCGEC

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Ensembles of best 7 models + GRECO + GTP-rerank	F0.5	72.8	—	Unverified
2	Majority-voting ensemble on best 7 models	F0.5	71.8	—	Unverified
3	GRECO (voting+ESC)	F0.5	71.12	—	Unverified
4	GEC-DI (LM+GED)	F0.5	69.6	—	Unverified
5	Unsupervised GEC + cLang8	F0.5	69.6	—	Unverified
6	ESC	F0.5	69.51	—	Unverified
7	T5	F0.5	68.87	—	Unverified
8	MoECE	F0.5	67.79	—	Unverified
9	SynGEC	F0.5	67.6	—	Unverified
10	Sequence tagging + token-level transformations + two-stage fine-tuning (+BERT, RoBERTa, XLNet)	F0.5	66.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Majority-voting ensemble on best 7 models	F0.5	81.4	—	Unverified
2	GRECO (voting+ESC)	F0.5	80.84	—	Unverified
3	ESC	F0.5	79.9	—	Unverified
4	RedPenNet	F0.5	77.6	—	Unverified
5	clang_large_ft2-gector	F0.5	77.1	—	Unverified
6	Unsupervised GEC + cLang8	F0.5	76.5	—	Unverified
7	DeBERTa + RoBERTa + XLNet	F0.5	76.05	—	Unverified
8	MoECE	F0.5	74.07	—	Unverified
9	Sequence tagging + token-level transformations + two-stage fine-tuning (+RoBERTa, XLNet)	F0.5	73.7	—	Unverified
10	BEA Combination	F0.5	73.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Llama + 1M BT + gold	F0.5	76.75	—	Unverified
2	mT5-based multimodal MoE	F0.5	76.3	—	Unverified
3	gT5 xxl	F0.5	75.96	—	Unverified
4	Transformer	F0.5	73.71	—	Unverified
5	Transformer - synthetic pretrain only	F0.5	51.41	—	Unverified
6	Multilayer Convolutional Encoder-Decoder	F0.5	43.35	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VERNet	GLEU	62.1	—	Unverified
2	Transformer + Pre-train with Pseudo Data + BERT	GLEU	62	—	Unverified
3	SMT + BiGRU	GLEU	61.5	—	Unverified
4	Copy-augmented Model (4 Ensemble +Denoising Autoencoder)	GLEU	61	—	Unverified
5	Transformer	GLEU	59.9	—	Unverified
6	CNN Seq2Seq	GLEU	57.47	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Llama + 1M BT + gold	F0.5	74.09	—	Unverified
2	mBART-based model with synthetic data	F0.5	68.17	—	Unverified
3	mT5 large + 10M synth	F0.5	68.09	—	Unverified
4	RedPenNet	F0.5	67.71	—	Unverified
5	ChatGPT (zero-shot)	F0.5	27.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GRECO (vote+ESC)	F0.5	85.21	—	Unverified
2	SMT + BiGRU	F0.5	72.04	—	Unverified
3	CNN Seq2Seq	F0.5	70.14	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN Seq2Seq + Quality Estimation	F0.5	56.52	—	Unverified
2	Transformer	F0.5	55.8	—	Unverified
3	+ BIFI with no critic	F0.5	18.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN Seq2Seq + Fluency Boost and inference	GLEU	62.37	—	Unverified
2	CNN Seq2Seq + Fluency Boost	F0.5	61.34	—	Unverified
3	+ BIFI (ours)	F0.5	42.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Transformer	GLEU	59.9	—	Unverified
2	CNN Seq2Seq	GLEU	57.47	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Llama + 1M BT + gold	F0.5	69.97	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	STG-Joint	exact match	34.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GEC-DI (LM+GED)	F0.5	48.61	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RedPenNet	F0.5	77.6	—	Unverified