Semorph: A Morphology Semantic Enhanced Pre-trained Model for Chinese Spam Text Detection-Reference-Cited by-同舟云学术

Semorph: A Morphology Semantic Enhanced Pre-trained Model for Chinese Spam Text Detection

Published:2022-10-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Information & Knowledge Management
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Author:

Lai Kaiting¹,Long Yinong²,Wu Bowen³,Li Ying⁴,Wang Baoxun²

Affiliation:

1. Peking University, Beijing, China

2. Platform and Content Group, Tencent, Beijing, China

3. Peking University & Platform and Content Group, Tencent, Beijing, China

4. National Research Center of Software Engineering, Peking University, Beijing, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3511808.3557448

Reference54 articles.

1. RCC: A Paradigm for Training a Robust Chinese Text Classification Model

2. A Bilingual Multi-type Spam Detection Model Based on M-BERT

3. Manifold Adversarial Augmentation for Neural Machine Translation

4. Glyph2Vec: Learning Chinese Out-of-Vocabulary Word Embedding from Glyphs

5. Alexis Conneau and Guillaume Lample . 2019. Cross-lingual language model pretraining. Advances in neural information processing systems 32 ( 2019 ). Alexis Conneau and Guillaume Lample. 2019. Cross-lingual language model pretraining. Advances in neural information processing systems 32 (2019).

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