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 376–400 of 415 papers

Title	Date	Tasks	Status
Grammatical error correction using hybrid systems and type filtering	Jun 1, 2014	Grammatical Error CorrectionLanguage Modelling	—Unverified
Correcting Preposition Errors in Learner English Using Error Case Frames and Feedback Messages	Jun 1, 2014	Grammatical Error CorrectionLanguage Modelling	—Unverified
Grammatical Error Detection and Correction using a Single Maximum Entropy Model	Jun 1, 2014	Grammatical Error CorrectionGrammatical Error Detection	—Unverified
Language Editing Dataset of Academic Texts	May 1, 2014	Grammatical Error Correction	—Unverified
Treelet Probabilities for HPSG Parsing and Error Correction	May 1, 2014	Grammatical Error CorrectionSentence	—Unverified
Generating artificial errors for grammatical error correction	Apr 1, 2014	Grammatical Error CorrectionMachine Translation	—Unverified
Building a State-of-the-Art Grammatical Error Correction System	Jan 1, 2014	Grammatical Error CorrectionMachine Translation	—Unverified
Correcting Serial Grammatical Errors based on N-grams and Syntax	Dec 1, 2013	Grammatical Error CorrectionLanguage Modelling	—Unverified
Grammatical Error Correction Using Feature Selection and Confidence Tuning	Oct 1, 2013	feature selectionGrammatical Error Correction	—Unverified
Joint Learning and Inference for Grammatical Error Correction	Oct 1, 2013	Grammatical Error Correction	—Unverified
Detecting English Grammatical Errors based on Machine Translation	Oct 1, 2013	Grammatical Error CorrectionGrammatical Error Detection	—Unverified
Constrained Grammatical Error Correction using Statistical Machine Translation	Aug 1, 2013	Grammatical Error CorrectionMachine Translation	—Unverified
CoNLL-2013 Shared Task: Grammatical Error Correction NTHU System Description	Aug 1, 2013	Grammatical Error Correction	—Unverified
NAIST at 2013 CoNLL Grammatical Error Correction Shared Task	Aug 1, 2013	Grammatical Error CorrectionLanguage Modelling	—Unverified
UdS at CoNLL 2013 Shared Task	Aug 1, 2013	Grammatical Error Correction	—Unverified
UM-Checker: A Hybrid System for English Grammatical Error Correction	Aug 1, 2013	Grammatical Error CorrectionGrammatical Error Detection	—Unverified
KUNLP Grammatical Error Correction System For CoNLL-2013 Shared Task	Aug 1, 2013	Grammatical Error Correction	—Unverified
Grammatical Error Correction Using Integer Linear Programming	Aug 1, 2013	Grammatical Error Correction	—Unverified
A Hybrid Model For Grammatical Error Correction	Aug 1, 2013	Grammatical Error CorrectionMeta-Learning	—Unverified
Toward More Precision in Correction of Grammatical Errors	Aug 1, 2013	Grammatical Error Correction	—Unverified
Grammatical Error Correction as Multiclass Classification with Single Model	Aug 1, 2013	ClassificationGeneral Classification	—Unverified
LFG-based Features for Noun Number and Article Grammatical Errors	Aug 1, 2013	Feature EngineeringGrammatical Error Correction	—Unverified
A Tree Transducer Model for Grammatical Error Correction	Aug 1, 2013	Grammatical Error CorrectionGrammatical Error Detection	—Unverified
Automated Collocation Suggestion for Japanese Second Language Learners	Aug 1, 2013	Grammatical Error Correction	—Unverified
IITB System for CoNLL 2013 Shared Task: A Hybrid Approach to Grammatical Error Correction	Aug 1, 2013	Grammatical Error CorrectionMachine Translation	—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