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Learning from Multiple Noisy Augmented Data Sets for Better
  Cross-Lingual Spoken Language Understanding

Learning from Multiple Noisy Augmented Data Sets for Better Cross-Lingual Spoken Language Understanding

3 September 2021
Yingmei Guo
Linjun Shou
J. Pei
Ming Gong
Mingxing Xu
Zhiyong Wu
Daxin Jiang
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Papers citing "Learning from Multiple Noisy Augmented Data Sets for Better Cross-Lingual Spoken Language Understanding"

3 / 3 papers shown
Title
UniPSDA: Unsupervised Pseudo Semantic Data Augmentation for Zero-Shot
  Cross-Lingual Natural Language Understanding
UniPSDA: Unsupervised Pseudo Semantic Data Augmentation for Zero-Shot Cross-Lingual Natural Language Understanding
Dongyang Li
Taolin Zhang
Jiali Deng
Longtao Huang
Chengyu Wang
Xiaofeng He
Hui Xue
26
1
0
24 Jun 2024
Unsupervised Cross-lingual Adaptation for Sequence Tagging and Beyond
Unsupervised Cross-lingual Adaptation for Sequence Tagging and Beyond
Xin Li
Lidong Bing
Wenxuan Zhang
Zheng Li
Wai Lam
37
25
0
23 Oct 2020
Data Augmentation using Pre-trained Transformer Models
Data Augmentation using Pre-trained Transformer Models
Varun Kumar
Ashutosh Choudhary
Eunah Cho
VLM
206
315
0
04 Mar 2020
1