|
--- |
|
language: |
|
- nl |
|
base_model: |
|
- FacebookAI/xlm-roberta-base |
|
pipeline_tag: token-classification |
|
tags: |
|
- coreference |
|
- resolution |
|
- gender |
|
- neutral |
|
- pronouns |
|
- debiading |
|
- dutch |
|
- CDA |
|
--- |
|
This Dutch coreference resolution model is based on the [wl-coref](https://github.com/vdobrovolskii/wl-coref) model. The model was debiased through CDA, in order to improve its performance on gender-neutral pronouns and neopronouns. We used [XLM-RoBERTa-base](https://huggingface.co/FacebookAI/xlm-roberta-base) as our base model, fine-tuned the model on the [SoNaR-1 corpus](https://taalmaterialen.ivdnt.org/download/tstc-sonar-corpus/), and then further fine-tuned the model on a gender-neutral version of the this corpus for debiasing purposes. We used five different seeds during our experiment, and upload all five versions of the model. |
|
|
|
For more information, see our [Github repository](https://github.com/gvanboven/Transforming_Dutch). |
|
|
|
This model was created as part of our FAccT 2024 paper. Find our published paper at https://dl.acm.org/doi/10.1145/3630106.3659049 and arxiv paper at https://arxiv.org/abs/2405.00134. |
|
|
|
## Usage |
|
For usage instructions for the wl-coref model, see [their repo](https://github.com/vdobrovolskii/wl-coref). |
|
|
|
## Citation |
|
G. van Boven, Y. Du, D. Nguyen, _Transforming Dutch: Debiasing Dutch Coreference Resolution Systems for Non-binary Pronouns_. FAccT 2024. |
|
|
|
``` |
|
@inproceedings{boven-2024-transforming, |
|
title = "Transforming Dutch: Debiasing Dutch Coreference Resolution Systems for Non-binary Pronouns", |
|
author = "van Boven, Goya and Du, Yupei and Nguyen, Dong", |
|
booktitle = "Proceedings of the 2024 Conference on Fairness, Accountability, and Transparency", |
|
month = jun, |
|
year = "2024", |
|
address = "Online and Rio de Janeiro, Brazil", |
|
publisher = "Association for Computing Machinery" |
|
} |
|
``` |
