Home Console Docs News Papers Tutorials Datasets Wiki SOTA LLM Models GPU Leaderboard Events

English

Grammatical Error Correction On Bea 2019 Test

Metrics

F0.5

Results

Performance results of various models on this benchmark

		Paper Title	Repository
Majority-voting ensemble on best 7 models	81.4	Pillars of Grammatical Error Correction: Comprehensive Inspection Of Contemporary Approaches In The Era of Large Language Models
GRECO (voting+ESC)	80.84	System Combination via Quality Estimation for Grammatical Error Correction
ESC	79.90	Frustratingly Easy System Combination for Grammatical Error Correction	-
RedPenNet	77.60	RedPenNet for Grammatical Error Correction: Outputs to Tokens, Attentions to Spans
clang_large_ft2-gector	77.1	Improved grammatical error correction by ranking elementary edits	-
Unsupervised GEC + cLang8	76.5	Unsupervised Grammatical Error Correction Rivaling Supervised Methods	-
DeBERTa + RoBERTa + XLNet	76.05	Ensembling and Knowledge Distilling of Large Sequence Taggers for Grammatical Error Correction
MoECE	74.07	Efficient and Interpretable Grammatical Error Correction with Mixture of Experts
Sequence tagging + token-level transformations + two-stage fine-tuning (+RoBERTa, XLNet)	73.7	GECToR -- Grammatical Error Correction: Tag, Not Rewrite
BEA Combination	73.2	Learning to combine Grammatical Error Corrections
GEC-DI (LM+GED)	73.1	Improving Seq2Seq Grammatical Error Correction via Decoding Interventions
LM-Critic	72.9	LM-Critic: Language Models for Unsupervised Grammatical Error Correction
Sequence tagging + token-level transformations + two-stage fine-tuning (+XLNet)	72.4	GECToR -- Grammatical Error Correction: Tag, Not Rewrite
Transformer + Pre-train with Pseudo Data	70.2	An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction
Transformer + Pre-train with Pseudo Data (+BERT)	69.8	Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction
Transformer	69.5	Neural Grammatical Error Correction Systems with Unsupervised Pre-training on Synthetic Data	-
Transformer	69.0	A Neural Grammatical Error Correction System Built On Better Pre-training and Sequential Transfer Learning
VERNet	68.9	Neural Quality Estimation with Multiple Hypotheses for Grammatical Error Correction
Ensemble of models	66.78	The LAIX Systems in the BEA-2019 GEC Shared Task	-

0 of 19 row(s) selected.

Grammatical Error Correction On Bea 2019 Test | SOTA | HyperAI