activity
20122022
most citedAugmenting Data with Mixup for Sentence Classification: An Empirical Study

145 citations · 218 across the 12 of their papers we have counts for

collaborators

18 papers

cs.LG2022

Cross Domain Few-Shot Learning via Meta Adversarial Training

Jirui Qi, Richong Zhang, Chune Li +1

Few-shot relation classification (RC) is one of the critical problems in machine learning. Current research merely focuses on the set-ups that both training and testing are from th…

cs.CL202247 cited

Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation

Qianben Chen, Richong Zhang, Yaowei Zheng +1

Contrastive learning has achieved remarkable success in representation learning via self-supervision in unsupervised settings. However, effectively adapting contrastive learning to…

cs.LG2021

Robust Regularization with Adversarial Labelling of Perturbed Samples

Xiaohui Guo, Richong Zhang, Yaowei Zheng +1

Recent researches have suggested that the predictive accuracy of neural network may contend with its adversarial robustness. This presents challenges in designing effective regular…

cs.LG2020

A Hypergradient Approach to Robust Regression without Correspondence

Yujia Xie, Yixiu Mao, Simiao Zuo +4

We consider a variant of regression problem, where the correspondence between input and output data is not available. Such shuffled data is commonly observed in many real world pro…

cs.LG20203 cited

On the Dynamics of Training Attention Models

Haoye Lu, Yongyi Mao, Amiya Nayak

The attention mechanism has been widely used in deep neural networks as a model component. By now, it has become a critical building block in many state-of-the-art natural language…

cs.CL2020

Parallel Interactive Networks for Multi-Domain Dialogue State Generation

Junfan Chen, Richong Zhang, Yongyi Mao +1

The dependencies between system and user utterances in the same turn and across different turns are not fully considered in existing multidomain dialogue state tracking (MDST) mode…