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 226–250 of 415 papers

Title	Date	Tasks	Status
面向汉语作为第二语言学习的个性化语法纠错(Personalizing Grammatical Error Correction for Chinese as a Second Language)	Oct 1, 2020	Grammatical Error Correction	—Unverified
Seq2Edits: Sequence Transduction Using Span-level Edit Operations	Sep 23, 2020	Grammatical Error CorrectionSentence	CodeCode Available
Data Weighted Training Strategies for Grammatical Error Correction	Aug 7, 2020	Grammatical Error CorrectionMachine Translation	—Unverified
Semantic Parsing for English as a Second Language	Jul 1, 2020	Grammatical Error CorrectionLanguage Acquisition	—Unverified
A Comparative Study of Synthetic Data Generation Methods for Grammatical Error Correction	Jul 1, 2020	Grammatical Error CorrectionMachine Translation	—Unverified
Grammatical Error Correction Using Pseudo Learner Corpus Considering Learner's Error Tendency	Jul 1, 2020	Grammatical Error Correction	—Unverified
Personalizing Grammatical Error Correction: Adaptation to Proficiency Level and L1	Jun 4, 2020	Grammatical Error Correction	—Unverified
Using Context in Neural Machine Translation Training Objectives	May 4, 2020	Grammatical Error CorrectionMachine Translation	—Unverified
Construction of an Evaluation Corpus for Grammatical Error Correction for Learners of Japanese as a Second Language	May 1, 2020	Grammatical Error CorrectionMachine Translation	—Unverified
Developing NLP Tools with a New Corpus of Learner Spanish	May 1, 2020	Grammatical Error Correction	—Unverified
Improving Readability for Automatic Speech Recognition Transcription	Apr 9, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Pseudo-Bidirectional Decoding for Local Sequence Transduction	Jan 31, 2020	DecoderGrammatical Error Correction	—Unverified
Towards Minimal Supervision BERT-based Grammar Error Correction	Jan 10, 2020	Grammatical Error CorrectionLanguage Modeling	—Unverified
GitHub Typo Corpus: A Large-Scale Multilingual Dataset of Misspellings and Grammatical Errors	Nov 28, 2019	Grammatical Error CorrectionSpelling Correction	CodeCode Available
Improving Grammatical Error Correction with Machine Translation Pairs	Nov 7, 2019	Grammatical Error CorrectionLanguage Modeling	CodeCode Available
Minimally-Augmented Grammatical Error Correction	Nov 1, 2019	Grammatical Error Correction	—Unverified
Diamonds in the Rough: Generating Fluent Sentences from Early-Stage Drafts for Academic Writing Assistance	Oct 21, 2019	Grammatical Error CorrectionSentence	CodeCode Available
Parallel Iterative Edit Models for Local Sequence Transduction	Oct 7, 2019	DecoderGrammatical Error Correction	CodeCode Available
Grammatical Error Correction in Low-Resource Scenarios	Oct 1, 2019	Grammatical Error CorrectionMachine Translation	CodeCode Available
Controllable Data Synthesis Method for Grammatical Error Correction	Sep 29, 2019	Grammatical Error Correction	—Unverified
Sequence-to-sequence Pre-training with Data Augmentation for Sentence Rewriting	Sep 13, 2019	Data AugmentationFormality Style Transfer	—Unverified
CUNI System for the Building Educational Applications 2019 Shared Task: Grammatical Error Correction	Sep 12, 2019	Grammatical Error CorrectionNMT	—Unverified
TEASPN: Framework and Protocol for Integrated Writing Assistance Environments	Sep 5, 2019	Grammatical Error Correction	CodeCode Available
An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction	Sep 2, 2019	Grammatical Error Correction	CodeCode Available
Denoising based Sequence-to-Sequence Pre-training for Text Generation	Aug 22, 2019	Abstractive Text SummarizationDecoder	—Unverified

Show:10 25 50

← PrevPage 10 of 17Next →

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