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@@ -6,14 +6,33 @@ license: apache-2.0
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  This is a fine-tuned LM in our papers below and the related GitHub repo is [here](https://github.com/metaphors/TibetanPLMsFineTuning).
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- ***[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)***
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- ***Multi-Granularity Tibetan Textual Adversarial Attack Method Based on Masked Language Model (Cao et al., WWW 2024 Workshop - SocialNLP)***
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  ## Citation
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  If you think our work useful, please kindly cite our paper.
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  ```
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  @inproceedings{cao-etal-2023-pay-attention,
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  title = "Pay Attention to the Robustness of {C}hinese Minority Language Models! Syllable-level Textual Adversarial Attack on {T}ibetan Script",
 
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  This is a fine-tuned LM in our papers below and the related GitHub repo is [here](https://github.com/metaphors/TibetanPLMsFineTuning).
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+ ***[Multi-Granularity Tibetan Textual Adversarial Attack Method Based on Masked Language Model (Cao et al., WWW 2024 Workshop - SocialNLP)](https://dl.acm.org/doi/10.1145/3589335.3652503)***
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+ ***[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)](https://aclanthology.org/2023.trustnlp-1.4)***
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  ## Citation
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  If you think our work useful, please kindly cite our paper.
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+ ```
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+ @inproceedings{10.1145/3589335.3652503,
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+ author = {Cao, Xi and Qun, Nuo and Gesang, Quzong and Zhu, Yulei and Nyima, Trashi},
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+ title = {Multi-Granularity Tibetan Textual Adversarial Attack Method Based on Masked Language Model},
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+ year = {2024},
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+ isbn = {9798400701726},
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+ publisher = {Association for Computing Machinery},
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+ address = {New York, NY, USA},
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+ url = {https://doi.org/10.1145/3589335.3652503},
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+ doi = {10.1145/3589335.3652503},
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+ booktitle = {Companion Proceedings of the ACM on Web Conference 2024},
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+ pages = {1672–1680},
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+ numpages = {9},
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+ keywords = {language model, robustness, textual adversarial attack, tibetan},
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+ location = {Singapore, Singapore},
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+ series = {WWW '24}
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+ }
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+ ```
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+
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  ```
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  @inproceedings{cao-etal-2023-pay-attention,
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  title = "Pay Attention to the Robustness of {C}hinese Minority Language Models! Syllable-level Textual Adversarial Attack on {T}ibetan Script",