SOTAVerified

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

Showing 1–50 of 415 papers

TitleStatusHype
An Extended Sequence Tagging Vocabulary for Grammatical Error CorrectionCode4
Mining Error Templates for Grammatical Error CorrectionCode2
CCTC: A Cross-Sentence Chinese Text Correction Dataset for Native SpeakersCode2
MuCGEC: a Multi-Reference Multi-Source Evaluation Dataset for Chinese Grammatical Error CorrectionCode2
Stronger Baselines for Grammatical Error Correction Using Pretrained Encoder-Decoder ModelCode1
Towards Automated Document Revision: Grammatical Error Correction, Fluency Edits, and BeyondCode1
Towards standardizing Korean Grammatical Error Correction: Datasets and AnnotationCode1
GrammarGPT: Exploring Open-Source LLMs for Native Chinese Grammatical Error Correction with Supervised Fine-TuningCode1
mEdIT: Multilingual Text Editing via Instruction TuningCode1
LM-Critic: Language Models for Unsupervised Grammatical Error CorrectionCode1
Rethinking Evaluation Metrics for Grammatical Error Correction: Why Use a Different Evaluation Process than Human?Code1
RobustGEC: Robust Grammatical Error Correction Against Subtle Context PerturbationCode1
Synthetic Data Generation for Grammatical Error Correction with Tagged Corruption ModelsCode1
The CoNLL-2014 Shared Task on Grammatical Error CorrectionCode1
Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error CorrectionCode1
ErAConD: Error Annotated Conversational Dialog Dataset for Grammatical Error CorrectionCode1
CoEdIT: Text Editing by Task-Specific Instruction TuningCode1
Ensembling and Knowledge Distilling of Large Sequence Taggers for Grammatical Error CorrectionCode1
FlaCGEC: A Chinese Grammatical Error Correction Dataset with Fine-grained Linguistic AnnotationCode1
GECTurk: Grammatical Error Correction and Detection Dataset for TurkishCode1
Improving Seq2Seq Grammatical Error Correction via Decoding InterventionsCode1
Linguistic Rules-Based Corpus Generation for Native Chinese Grammatical Error CorrectionCode1
NaSGEC: a Multi-Domain Chinese Grammatical Error Correction Dataset from Native Speaker TextsCode1
Pillars of Grammatical Error Correction: Comprehensive Inspection Of Contemporary Approaches In The Era of Large Language ModelsCode1
Revisiting Grammatical Error Correction Evaluation and BeyondCode1
Chinese grammatical error correction based on knowledge distillationCode1
Alirector: Alignment-Enhanced Chinese Grammatical Error CorrectorCode1
SynGEC: Syntax-Enhanced Grammatical Error Correction with a Tailored GEC-Oriented ParserCode1
System Combination via Quality Estimation for Grammatical Error CorrectionCode1
Tail-to-Tail Non-Autoregressive Sequence Prediction for Chinese Grammatical Error CorrectionCode1
CLEME2.0: Towards More Interpretable Evaluation by Disentangling Edits for Grammatical Error CorrectionCode1
Detection-Correction Structure via General Language Model for Grammatical Error CorrectionCode1
Are Pre-trained Language Models Useful for Model Ensemble in Chinese Grammatical Error Correction?Code1
CLEME: Debiasing Multi-reference Evaluation for Grammatical Error CorrectionCode1
Advancements in Arabic Grammatical Error Detection and Correction: An Empirical InvestigationCode1
Document-level grammatical error correctionCode1
A Simple Recipe for Multilingual Grammatical Error CorrectionCode1
Enhancing Grammatical Error Correction Systems with ExplanationsCode1
Automatic Error Type Annotation for ArabicCode1
A Survey on Non-Autoregressive Generation for Neural Machine Translation and BeyondCode1
Frustratingly Easy System Combination for Grammatical Error CorrectionCode1
GECToR -- Grammatical Error Correction: Tag, Not RewriteCode1
Improved grammatical error correction by ranking elementary editsCode1
Improving Iterative Text Revision by Learning Where to Edit from Other Revision TasksCode1
Instantaneous Grammatical Error Correction with Shallow Aggressive DecodingCode1
Interpretability for Language Learners Using Example-Based Grammatical Error CorrectionCode1
MixEdit: Revisiting Data Augmentation and Beyond for Grammatical Error CorrectionCode1
FCGEC: Fine-Grained Corpus for Chinese Grammatical Error CorrectionCode1
Neural Quality Estimation with Multiple Hypotheses for Grammatical Error CorrectionCode1
UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian LanguageCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Ensembles of best 7 models + GRECO + GTP-rerankF0.572.8—Unverified
2Majority-voting ensemble on best 7 modelsF0.571.8—Unverified
3GRECO (voting+ESC)F0.571.12—Unverified
4GEC-DI (LM+GED)F0.569.6—Unverified
5Unsupervised GEC + cLang8F0.569.6—Unverified
6ESCF0.569.51—Unverified
7T5F0.568.87—Unverified
8MoECEF0.567.79—Unverified
9SynGECF0.567.6—Unverified
10Sequence tagging + token-level transformations + two-stage fine-tuning (+BERT, RoBERTa, XLNet)F0.566.5—Unverified
#ModelMetricClaimedVerifiedStatus
1Majority-voting ensemble on best 7 modelsF0.581.4—Unverified
2GRECO (voting+ESC)F0.580.84—Unverified
3ESCF0.579.9—Unverified
4RedPenNetF0.577.6—Unverified
5clang_large_ft2-gectorF0.577.1—Unverified
6Unsupervised GEC + cLang8F0.576.5—Unverified
7DeBERTa + RoBERTa + XLNetF0.576.05—Unverified
8MoECEF0.574.07—Unverified
9Sequence tagging + token-level transformations + two-stage fine-tuning (+RoBERTa, XLNet)F0.573.7—Unverified
10BEA CombinationF0.573.2—Unverified
#ModelMetricClaimedVerifiedStatus
1Llama + 1M BT + goldF0.576.75—Unverified
2mT5-based multimodal MoEF0.576.3—Unverified
3gT5 xxlF0.575.96—Unverified
4TransformerF0.573.71—Unverified
5Transformer - synthetic pretrain onlyF0.551.41—Unverified
6Multilayer Convolutional Encoder-DecoderF0.543.35—Unverified
#ModelMetricClaimedVerifiedStatus
1VERNetGLEU62.1—Unverified
2Transformer + Pre-train with Pseudo Data + BERTGLEU62—Unverified
3SMT + BiGRUGLEU61.5—Unverified
4Copy-augmented Model (4 Ensemble +Denoising Autoencoder)GLEU61—Unverified
5TransformerGLEU59.9—Unverified
6CNN Seq2SeqGLEU57.47—Unverified
#ModelMetricClaimedVerifiedStatus
1Llama + 1M BT + goldF0.574.09—Unverified
2mBART-based model with synthetic dataF0.568.17—Unverified
3mT5 large + 10M synthF0.568.09—Unverified
4RedPenNetF0.567.71—Unverified
5ChatGPT (zero-shot)F0.527.4—Unverified
#ModelMetricClaimedVerifiedStatus
1GRECO (vote+ESC)F0.585.21—Unverified
2SMT + BiGRUF0.572.04—Unverified
3CNN Seq2SeqF0.570.14—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN Seq2Seq + Quality EstimationF0.556.52—Unverified
2TransformerF0.555.8—Unverified
3+ BIFI with no criticF0.518.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN Seq2Seq + Fluency Boost and inferenceGLEU62.37—Unverified
2CNN Seq2Seq + Fluency BoostF0.561.34—Unverified
3+ BIFI (ours)F0.542.4—Unverified
#ModelMetricClaimedVerifiedStatus
1TransformerGLEU59.9—Unverified
2CNN Seq2SeqGLEU57.47—Unverified
#ModelMetricClaimedVerifiedStatus
1Llama + 1M BT + goldF0.569.97—Unverified
#ModelMetricClaimedVerifiedStatus
1STG-Jointexact match34.1—Unverified
#ModelMetricClaimedVerifiedStatus
1GEC-DI (LM+GED)F0.548.61—Unverified
#ModelMetricClaimedVerifiedStatus
1RedPenNetF0.577.6—Unverified