3 citations · 3 across the 6 of their papers we have counts for
7 papers
A Diversity-Enhanced and Constraints-Relaxed Augmentation for Low-Resource Classification
Guang Liu, Hailong Huang, Yuzhao Mao +3
Data augmentation (DA) aims to generate constrained and diversified data to improve classifiers in Low-Resource Classification (LRC). Previous studies mostly use a fine-tuned Langu…
Adversarial Mixing Policy for Relaxing Locally Linear Constraints in Mixup
Guang Liu, Yuzhao Mao, Hailong Huang +2
Mixup is a recent regularizer for current deep classification networks. Through training a neural network on convex combinations of pairs of examples and their labels, it imposes l…
DialogueTRM: Exploring the Intra- and Inter-Modal Emotional Behaviors in the Conversation
Yuzhao Mao, Qi Sun, Guang Liu +4
Emotion Recognition in Conversations (ERC) is essential for building empathetic human-machine systems. Existing studies on ERC primarily focus on summarizing the context informatio…
A Partial Regularization Method for Network Compression
E Zhenqian, Gao Weiguo
Deep Neural Networks have achieved remarkable success relying on the developing availability of GPUs and large-scale datasets with increasing network depth and width. However, due…
Hierarchical Context Enhanced Multi-Domain Dialogue System for Multi-domain Task Completion
Jingyuan Yang, Guang Liu, Yuzhao Mao +5
Task 1 of the DSTC8-track1 challenge aims to develop an end-to-end multi-domain dialogue system to accomplish complex users' goals under tourist information desk settings. This pap…
An Improving Framework of regularization for Network Compression
E Zhenqian, Gao Weiguo
Deep Neural Networks have achieved remarkable success relying on the developing high computation capability of GPUs and large-scale datasets with increasing network depth and width…