110 citations · 867 across the 51 of their papers we have counts for
7 papers · 1 filter
Explicit Sparse Transformer: Concentrated Attention Through Explicit Selection
Guangxiang Zhao, Junyang Lin, Zhiyuan Zhang +3
Self-attention based Transformer has demonstrated the state-of-the-art performances in a number of natural language processing tasks. Self-attention is able to model long-term depe…
An Adaptive and Momental Bound Method for Stochastic Learning
Jianbang Ding, Xuancheng Ren, Ruixuan Luo +1
Training deep neural networks requires intricate initialization and careful selection of learning rates. The emergence of stochastic gradient optimization methods that use adaptive…
Incorporating Fine-grained Events in Stock Movement Prediction
Deli Chen, Yanyan Zou, Keiko Harimoto +3
Considering event structure information has proven helpful in text-based stock movement prediction. However, existing works mainly adopt the coarse-grained events, which loses the…
A Hierarchical Reinforced Sequence Operation Method for Unsupervised Text Style Transfer
Chen Wu, Xuancheng Ren, Fuli Luo +1
Unsupervised text style transfer aims to alter text styles while preserving the content, without aligned data for supervision. Existing seq2seq methods face three challenges: 1) th…
PKUSEG: A Toolkit for Multi-Domain Chinese Word Segmentation
Ruixuan Luo, Jingjing Xu, Yi Zhang +3
Chinese word segmentation (CWS) is a fundamental step of Chinese natural language processing. In this paper, we build a new toolkit, named PKUSEG, for multi-domain word segmentatio…
Memorized Sparse Backpropagation
Zhiyuan Zhang, Pengcheng Yang, Xuancheng Ren +2
Neural network learning is usually time-consuming since backpropagation needs to compute full gradients and backpropagate them across multiple layers. Despite its success of existi…
Aligning Visual Regions and Textual Concepts for Semantic-Grounded Image Representations
Fenglin Liu, Yuanxin Liu, Xuancheng Ren +2
In vision-and-language grounding problems, fine-grained representations of the image are considered to be of paramount importance. Most of the current systems incorporate visual fe…