
## Introduction

This is a fine-tuned LM in our paper below and the related GitHub repo is [here](https://github.com/metaphors/TibetanPLMsFineTuning).

***[Pay Attention to the Robustness of Chinese Minority Language Models! Syllable-level Textual Adversarial Attack on Tibetan Script](https://aclanthology.org/2023.trustnlp-1.4) (Cao et al., ACL 2023 Workshop - TrustNLP)***

## Citation

If you think our work useful, please kindly cite our paper.

```
@inproceedings{cao-etal-2023-pay-attention,
    title = "Pay Attention to the Robustness of {C}hinese Minority Language Models! Syllable-level Textual Adversarial Attack on {T}ibetan Script",
    author = "Cao, Xi  and
      Dawa, Dolma  and
      Qun, Nuo  and
      Nyima, Trashi",
    booktitle = "Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing (TrustNLP 2023)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.trustnlp-1.4",
    pages = "35--46"
}
```
{"license": "apache-2.0"}
transformers pytorch xlm-roberta text-classification license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #xlm-roberta #text-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 


## Introduction

This is a fine-tuned LM in our paper below and the related GitHub repo is here.

*Pay Attention to the Robustness of Chinese Minority Language Models! Syllable-level Textual Adversarial Attack on Tibetan Script (Cao et al., ACL 2023 Workshop - TrustNLP)*

If you think our work useful, please kindly cite our paper.


## Introduction

This is a fine-tuned LM in our paper below and the related GitHub repo is here.

*Pay Attention to the Robustness of Chinese Minority Language Models! Syllable-level Textual Adversarial Attack on Tibetan Script (Cao et al., ACL 2023 Workshop - TrustNLP)*

If you think our work useful, please kindly cite our paper.
TAGS
#transformers #pytorch #xlm-roberta #text-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ## Introduction

This is a fine-tuned LM in our paper below and the related GitHub repo is here.

*Pay Attention to the Robustness of Chinese Minority Language Models! Syllable-level Textual Adversarial Attack on Tibetan Script (Cao et al., ACL 2023 Workshop - TrustNLP)*

If you think our work useful, please kindly cite our paper.