118 citations · 199 across the 20 of their papers we have counts for
5 papers · 1 filter
Self-Training with Differentiable Teacher
Simiao Zuo, Yue Yu, Chen Liang +5
Self-training achieves enormous success in various semi-supervised and weakly-supervised learning tasks. The method can be interpreted as a teacher-student framework, where the tea…
ARCH: Efficient Adversarial Regularized Training with Caching
Simiao Zuo, Chen Liang, Haoming Jiang +5
Adversarial regularization can improve model generalization in many natural language processing tasks. However, conventional approaches are computationally expensive since they nee…
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization
Chen Liang, Simiao Zuo, Minshuo Chen +5
The Lottery Ticket Hypothesis suggests that an over-parametrized network consists of ``lottery tickets'', and training a certain collection of them (i.e., a subnetwork) can match t…
Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach
Simiao Zuo, Chen Liang, Haoming Jiang +5
Adversarial regularization has been shown to improve the generalization performance of deep learning models in various natural language processing tasks. Existing works usually for…
Token-wise Curriculum Learning for Neural Machine Translation
Chen Liang, Haoming Jiang, Xiaodong Liu +4
Existing curriculum learning approaches to Neural Machine Translation (NMT) require sampling sufficient amounts of "easy" samples from training data at the early training stage. Th…