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Grammatical Error Correction On Conll 2014

Métriques

F0.5
Precision
Recall

Résultats

Résultats de performance de divers modèles sur ce benchmark

Paper Title
Ensembles of best 7 models + GRECO + GTP-rerank72.883.947.5Pillars of Grammatical Error Correction: Comprehensive Inspection Of Contemporary Approaches In The Era of Large Language Models
Majority-voting ensemble on best 7 models71.883.745.7Pillars of Grammatical Error Correction: Comprehensive Inspection Of Contemporary Approaches In The Era of Large Language Models
GRECO (voting+ESC)71.1279.649.86System Combination via Quality Estimation for Grammatical Error Correction
GEC-DI (LM+GED)69.679.246.8Improving Seq2Seq Grammatical Error Correction via Decoding Interventions
Unsupervised GEC + cLang869.675.053.8Unsupervised Grammatical Error Correction Rivaling Supervised Methods
ESC69.5181.4843.78Frustratingly Easy System Combination for Grammatical Error Correction
T568.87--A Simple Recipe for Multilingual Grammatical Error Correction
MoECE67.7974.2950.21Efficient and Interpretable Grammatical Error Correction with Mixture of Experts
SynGEC67.674.749.0SynGEC: Syntax-Enhanced Grammatical Error Correction with a Tailored GEC-Oriented Parser
Sequence tagging + token-level transformations + two-stage fine-tuning (+BERT, RoBERTa, XLNet)66.578.241.5GECToR -- Grammatical Error Correction: Tag, Not Rewrite
LM-Critic65.8--LM-Critic: Language Models for Unsupervised Grammatical Error Correction
Sequence tagging + token-level transformations + two-stage fine-tuning (+XLNet)65.377.540.1GECToR -- Grammatical Error Correction: Tag, Not Rewrite
Transformer + Pre-train with Pseudo Data (+BERT)65.2--Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction
Transformer + Pre-train with Pseudo Data65.0--An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction
VERNet63.7--Neural Quality Estimation with Multiple Hypotheses for Grammatical Error Correction
BART63.069.945.1Stronger Baselines for Grammatical Error Correction Using Pretrained Encoder-Decoder Model
Sequence Labeling with edits using BERT, Faster inference61.2--Parallel Iterative Edit Models for Local Sequence Transduction
Copy-augmented Model (4 Ensemble +Denoising Autoencoder)61.1571.5738.65Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data
Sequence Labeling with edits using BERT, Faster inference (Single Model)59.7--Parallel Iterative Edit Models for Local Sequence Transduction
CNN Seq2Seq + Quality Estimation56.52--Neural Quality Estimation of Grammatical Error Correction
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