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Asian Low-Resour. Lang. Inf. Process."],"published-print":{"date-parts":[[2023,8,31]]},"abstract":"<jats:p>Text classification is a critical and foundational task in Tibetan natural language processing, it plays a crucial role in various applications, such as sentiment analysis and information extraction. However, the limited availability of annotated data poses a significant challenge to Tibetan natural language processing. This paper proposes a prompt learning-based method for low-resource Tibetan text classification to overcome this challenge. This method utilizes pre-trained language models to learn text representation and generation capabilities on a large-scale unsupervised Tibetan corpus, enabling few-shot Tibetan text classification. Experimental results demonstrate that the proposed method significantly improves the performance of Tibetan text classification in low-resource scenarios. This work provides a new research idea and method for low-resource language processing, such as Tibetan natural language processing. Hopefully, it will inspire subsequent work on low-resource language processing.<\/jats:p>","DOI":"10.1145\/3603168","type":"journal-article","created":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T11:25:12Z","timestamp":1685532312000},"page":"1-13","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Prompt-based for Low-Resource Tibetan Text Classification"],"prefix":"10.1145","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0805-4268","authenticated-orcid":false,"given":"Bo","family":"An","sequence":"first","affiliation":[{"name":"Institute of Ethnology and Anthropology, Chinese Academy of Social Sciences, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,8,24]]},"reference":[{"key":"e_1_3_2_2_1","unstructured":"Li Ailin. 2014. Research on Tibetan text classification algorithm for Web public opinion analysis. 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