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 176–200 of 415 papers

Title	Date	Tasks	Status	Hype
New Dataset and Strong Baselines for the Grammatical Error Correction of Russian	Aug 1, 2021	Grammatical Error Correction	—Unverified	0
A Study of Morphological Robustness of Neural Machine Translation	Aug 1, 2021	Grammatical Error CorrectionMachine Translation	CodeCode Available	0
基于字词粒度噪声数据增强的中文语法纠错(Chinese Grammatical Error Correction enhanced by Data Augmentation from Word and Character Levels)	Aug 1, 2021	Data AugmentationGrammatical Error Correction	—Unverified	0
Instantaneous Grammatical Error Correction with Shallow Aggressive Decoding	Jun 9, 2021	DecoderGrammatical Error Correction	CodeCode Available	1
A Simple Recipe for Multilingual Grammatical Error Correction	Jun 7, 2021	Grammatical Error Correction	CodeCode Available	1
Do Grammatical Error Correction Models Realize Grammatical Generalization?	Jun 6, 2021	Grammatical Error Correction	—Unverified	0
Tail-to-Tail Non-Autoregressive Sequence Prediction for Chinese Grammatical Error Correction	Jun 3, 2021	Grammatical Error CorrectionSentence	CodeCode Available	1
Negative language transfer in learner English: A new dataset	Jun 1, 2021	Grammatical Error CorrectionLanguage Acquisition	CodeCode Available	0
Grammatical Error Correction as GAN-like Sequence Labeling	May 29, 2021	Grammatical Error Correction	—Unverified	0
Synthetic Data Generation for Grammatical Error Correction with Tagged Corruption Models	May 27, 2021	DiversityGrammatical Error Correction	CodeCode Available	1
Neural Predictive Text for Grammatical Error Prevention	May 16, 2021	Grammatical Error CorrectionLanguage Modeling	—Unverified	0
Neural Quality Estimation with Multiple Hypotheses for Grammatical Error Correction	May 10, 2021	Grammatical Error CorrectionGrammatical Error Detection	CodeCode Available	1
Leveraging Task Information in Grammatical Error Correction for Short Answer Assessment through Context-based Reranking	May 1, 2021	Grammatical Error CorrectionReranking	—Unverified	0
Grammatical Error Generation Based on Translated Fragments	Apr 20, 2021	Grammatical Error CorrectionMachine Translation	—Unverified	0
Comparison of Grammatical Error Correction Using Back-Translation Models	Apr 16, 2021	Grammatical Error CorrectionTranslation	—Unverified	0
Document-level grammatical error correction	Apr 1, 2021	Grammatical Error CorrectionNMT	CodeCode Available	1
Data Strategies for Low-Resource Grammatical Error Correction	Apr 1, 2021	Grammatical Error Correction	—Unverified	0
How Good (really) are Grammatical Error Correction Systems?	Apr 1, 2021	Grammatical Error Correction	—Unverified	0
UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian Language	Mar 31, 2021	Grammatical Error Correction	CodeCode Available	1
Few-Shot Domain Adaptation for Grammatical Error Correction via Meta-Learning	Jan 29, 2021	Domain AdaptationGrammatical Error Correction	—Unverified	0
Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning	Dec 29, 2020	DecoderGrammatical Error Correction	CodeCode Available	1
BERT Enhanced Neural Machine Translation and Sequence Tagging Model for Chinese Grammatical Error Diagnosis	Dec 1, 2020	Grammatical Error CorrectionMachine Translation	—Unverified	0
Non-Autoregressive Grammatical Error Correction Toward a Writing Support System	Dec 1, 2020	Grammatical Error Correction	—Unverified	0
TMU-NLP System Using BERT-based Pre-trained Model to the NLP-TEA CGED Shared Task 2020	Dec 1, 2020	DecoderGrammatical Error Correction	—Unverified	0
Chinese Grammatical Error Detection Based on BERT Model	Dec 1, 2020	Binary 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