transformers pytorch deberta-v2 greco grammar grammaticality gec en arxiv:2310.14947 base_model:microsoft/deberta-v3-large license:gpl-3.0 endpoints_compatible region:us
---
language: en
tags:
- greco
- grammar
- grammaticality
- gec
base_model: microsoft/deberta-v3-large
license: gpl-3.0
---

# GRECO: Gammaticality-scorer for re-ranking corrections
GRECO is a quality estimation model for grammatical error correction. The model is trained to detect which words are incorrect and whether a word or phrase needs to be inserted after certain words. You can then use the model to get the grammaticality score of a sentence.

Please check the [official repository](https://github.com/nusnlp/greco/tree/main) for more implementation details and updates.

The model was published in the following paper:
> System Combination via Quality Estimation for Grammatical Error Correction ([PDF](https://arxiv.org/abs/2310.14947) | [ACL Anthology](https://aclanthology.org/2023.emnlp-main.785/)) <br>
> [Muhammad Reza Qorib](https://mrqorib.github.io/) and [Hwee Tou Ng](https://www.comp.nus.edu.sg/~nght/) <br>
> The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP)

## Citation
If you find it useful for your work, please cite the paper:
```latex
@inproceedings{qorib-ng-2023-system,
    title = "System Combination via Quality Estimation for Grammatical Error Correction",
    author = "Qorib, Muhammad Reza  and
      Ng, Hwee Tou",
    editor = "Bouamor, Houda  and
      Pino, Juan  and
      Bali, Kalika",
    booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2023",
    address = "Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.emnlp-main.785",
    doi = "10.18653/v1/2023.emnlp-main.785",
    pages = "12746--12759",
}
```
