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Grammatical Error Detection

Grammatical Error Detection (GED) is the task of detecting different kinds of errors in text such as spelling, punctuation, grammatical, and word choice errors. Grammatical error detection (GED) is one of the key component in grammatical error correction (GEC) community.

Papers

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Showing 76–100 of 100 papers

TitleStatusHype
LinggleWrite: a Coaching System for Essay Writing—0
Model Combination for Correcting Preposition Selection Errors—0
Multi-Head Multi-Layer Attention to Deep Language Representations for Grammatical Error Detection—0
NAIST at the HOO 2012 Shared Task—0
NAIST at the NLI 2013 Shared Task—0
Neural Models for Predicting Celtic Mutations—0
Neural Multi-task Learning in Automated Assessment—0
Neural sequence modelling for learner error prediction—0
Oddballness: universal anomaly detection with language models—0
Overview of the NLP-TEA 2015 Shared Task for Chinese Grammatical Error Diagnosis—0
Precision Isn't Everything: A Hybrid Approach to Grammatical Error Detection—0
Problems in Evaluating Grammatical Error Detection Systems—0
RACAI GEC -- A hybrid approach to Grammatical Error Correction—0
Semi-automatically Annotated Learner Corpus for Russian—0
Grammatical Error Detection Using Error- and Grammaticality-Specific Word EmbeddingsCode0
Towards a standard evaluation method for grammatical error detection and correctionCode0
Probing for targeted syntactic knowledge through grammatical error detectionCode0
Wronging a Right: Generating Better Errors to Improve Grammatical Error DetectionCode0
The Tembusu Treebank: An English Learner TreebankCode0
Evaluation of really good grammatical error correctionCode0
Enhancing Grammatical Error Detection using BERT with Cleaned Lang-8 DatasetCode0
Detecting Local Insights from Global Labels: Supervised & Zero-Shot Sequence Labeling via a Convolutional DecompositionCode0
Bangla Grammatical Error Detection Using T5 Transformer ModelCode0
Multi-Class Grammatical Error Detection for Correction: A Tale of Two SystemsCode0
Sequence Classification with Human AttentionCode0
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