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 126–150 of 415 papers

Title	Date	Tasks	Status	Hype
Improving Grammatical Error Correction for Multiword Expressions	Jun 1, 2022	DecoderGrammatical Error Correction	—Unverified	0
Enriching Grammatical Error Correction Resources for Modern Greek	Jun 1, 2022	Grammatical Error Correction	—Unverified	0
Developing a Spell and Grammar Checker for Icelandic using an Error Corpus	Jun 1, 2022	Grammatical Error CorrectionSentence	—Unverified	0
Semi-automatically Annotated Learner Corpus for Russian	Jun 1, 2022	Grammatical Error CorrectionGrammatical Error Detection	—Unverified	0
MTee: Open Machine Translation Platform for Estonian Government	Jun 1, 2022	Document TranslationGrammatical Error Correction	—Unverified	0
EdiT5: Semi-Autoregressive Text-Editing with T5 Warm-Start	May 24, 2022	DecoderGrammatical Error Correction	—Unverified	0
Towards Automated Document Revision: Grammatical Error Correction, Fluency Edits, and Beyond	May 23, 2022	Grammatical Error CorrectionLanguage Modelling	CodeCode Available	1
Sequence-to-Action: Grammatical Error Correction with Action Guided Sequence Generation	May 22, 2022	Grammatical Error CorrectionSentence	—Unverified	0
Lossless Acceleration for Seq2seq Generation with Aggressive Decoding	May 20, 2022	Abstractive Text SummarizationGPU	CodeCode Available	0
Some Grammatical Errors are Frequent, Others are Important	May 11, 2022	Grammatical Error Correction	CodeCode Available	0
Adjusting the Precision-Recall Trade-Off with Align-and-Predict Decoding for Grammatical Error Correction	May 1, 2022	Grammatical Error Correction	CodeCode Available	0
“Is Whole Word Masking Always Better for Chinese BERT?”: Probing on Chinese Grammatical Error Correction	May 1, 2022	Grammatical Error CorrectionLanguage Modeling	—Unverified	0
A New Evaluation Method: Evaluation Data and Metrics for Chinese Grammar Error Correction	Apr 30, 2022	Chinese Word SegmentationGrammatical Error Correction	—Unverified	0
MuCGEC: a Multi-Reference Multi-Source Evaluation Dataset for Chinese Grammatical Error Correction	Apr 23, 2022	Grammatical Error CorrectionSentence	CodeCode Available	2
A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond	Apr 20, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	1
BLISS: Robust Sequence-to-Sequence Learning via Self-Supervised Input Representation	Apr 16, 2022	DecoderGrammatical Error Correction	—Unverified	0
Uncertainty Determines the Adequacy of the Mode and the Tractability of Decoding in Sequence-to-Sequence Models	Apr 1, 2022	Grammatical Error CorrectionMachine Translation	—Unverified	0
Ensembling and Knowledge Distilling of Large Sequence Taggers for Grammatical Error Correction	Mar 24, 2022	Grammatical Error CorrectionKnowledge Distillation	CodeCode Available	1
Towards Lithuanian grammatical error correction	Mar 18, 2022	Grammatical Error Correction	CodeCode Available	0
Type-Driven Multi-Turn Corrections for Grammatical Error Correction	Mar 17, 2022	Data AugmentationGrammatical Error Correction	CodeCode Available	0
Interpretability for Language Learners Using Example-Based Grammatical Error Correction	Mar 14, 2022	Grammatical Error Correction	CodeCode Available	1
"Is Whole Word Masking Always Better for Chinese BERT?": Probing on Chinese Grammatical Error Correction	Mar 1, 2022	Grammatical Error CorrectionLanguage Modeling	—Unverified	0
EdgeFormer: A Parameter-Efficient Transformer for On-Device Seq2seq Generation	Feb 16, 2022	Grammatical Error CorrectionKnowledge Distillation	—Unverified	0
Error Correction in ASR using Sequence-to-Sequence Models	Feb 2, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
A Unified Strategy for Multilingual Grammatical Error Correction with Pre-trained Cross-Lingual Language Model	Jan 26, 2022	Grammatical Error CorrectionLanguage Modeling	CodeCode Available	0

Show:10 25 50

← PrevPage 6 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