Papers with Grammatical Error Detection
Zero-shot Cross-Lingual Transfer for Synthetic Data Generation in Grammatical Error Detection (2024.emnlp-main)
Copied to clipboard
| Challenge: | Existing methods for Grammatical Error Detection (GED) rely on human annotations, but these are unavailable in many low-resource languages. |
| Approach: | They propose a two-stage fine-tuning pipeline to train a GED model using synthetic errors from target languages and human-annotated GED corpora from source languages. |
| Outcome: | The proposed method outperforms current state-of-the-art annotation-free GED methods and produces errors that are more diverse and similar to human errors. |
A Representation Level Analysis of NMT Model Robustness to Grammatical Errors (2025.findings-acl)
Copied to clipboard
| Challenge: | Existing work on robustness failures or improving robustness has focused on documenting failures . however, there has been limited analysis of model representations in response to noise. |
| Approach: | They perform Grammatical Error Detection probing and representational similarity analysis to examine model representations of ungrammatical inputs and how they evolve through model layers. |
| Outcome: | The proposed model detects and corrects the grammatical error by moving its representation toward the correct form. |