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

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Showing 301–325 of 415 papers

Title	Date	Tasks	Status
Improving Grammatical Error Correction Models with Purpose-Built Adversarial Examples	Nov 1, 2020	Grammatical Error CorrectionSentence	—Unverified
Improving Grammatical Error Correction with Data Augmentation by Editing Latent Representation	Dec 1, 2020	Data AugmentationDiversity	—Unverified
Improving Precision of Grammatical Error Correction with a Cheat Sheet	Aug 1, 2019	Grammatical Error CorrectionMachine Translation	—Unverified
Improving Readability for Automatic Speech Recognition Transcription	Apr 9, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Improving the Efficiency of Grammatical Error Correction with Erroneous Span Detection and Correction	Oct 7, 2020	Grammatical Error CorrectionSentence	—Unverified
Is ChatGPT a Highly Fluent Grammatical Error Correction System? A Comprehensive Evaluation	Apr 4, 2023	Grammatical Error CorrectionIn-Context Learning	—Unverified
"Is Whole Word Masking Always Better for Chinese BERT?": Probing on Chinese Grammatical Error Correction	Nov 16, 2021	Grammatical Error CorrectionLanguage Modeling	—Unverified
"Is Whole Word Masking Always Better for Chinese BERT?": Probing on Chinese Grammatical Error Correction	Mar 1, 2022	Grammatical Error CorrectionLanguage Modeling	—Unverified
“Is Whole Word Masking Always Better for Chinese BERT?”: Probing on Chinese Grammatical Error Correction	May 1, 2022	Grammatical Error CorrectionLanguage Modeling	—Unverified
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
Joint Learning and Inference for Grammatical Error Correction	Oct 1, 2013	Grammatical Error Correction	—Unverified
Judge a Sentence by Its Content to Generate Grammatical Errors	Aug 20, 2022	Grammatical Error CorrectionSentence	—Unverified
Keynote Lecture 2: Grammatical Error Correction: Past, Present and Future	Dec 1, 2017	Grammatical Error Correction	—Unverified
KUNLP Grammatical Error Correction System For CoNLL-2013 Shared Task	Aug 1, 2013	Grammatical Error Correction	—Unverified
Language Editing Dataset of Academic Texts	May 1, 2014	Grammatical Error Correction	—Unverified
Language Model Based Grammatical Error Correction without Annotated Training Data	Jun 1, 2018	Grammatical Error CorrectionLanguage Modeling	—Unverified
Large Language Models Are State-of-the-Art Evaluator for Grammatical Error Correction	Mar 26, 2024	Grammatical Error CorrectionMachine Translation	—Unverified
Leveraging Denoised Abstract Meaning Representation for Grammatical Error Correction	Jul 5, 2023	Abstract Meaning RepresentationDenoising	—Unverified
Leveraging Task Information in Grammatical Error Correction for Short Answer Assessment through Context-based Reranking	May 1, 2021	Grammatical Error CorrectionReranking	—Unverified
LFG-based Features for Noun Number and Article Grammatical Errors	Aug 1, 2013	Feature EngineeringGrammatical Error Correction	—Unverified
Linguistic Features of Helpfulness in Automated Support for Creative Writing	Jun 1, 2018	Grammatical Error CorrectionStory Generation	—Unverified
LLM-based Code-Switched Text Generation for Grammatical Error Correction	Oct 14, 2024	Grammatical Error CorrectionSynthetic Data Generation	—Unverified
LLMCL-GEC: Advancing Grammatical Error Correction with LLM-Driven Curriculum Learning	Dec 17, 2024	Grammatical Error Correction	—Unverified
Loss-Aware Curriculum Learning for Chinese Grammatical Error Correction	Dec 31, 2024	Grammatical Error Correction	—Unverified
Memory-based Grammatical Error Correction	Aug 1, 2013	Grammatical Error Correction	—Unverified

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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