1.5k citations · 5.2k across the 127 of their papers we have counts for
12 papers · 1 filter
Switch-LSTMs for Multi-Criteria Chinese Word Segmentation
Jingjing Gong, Xinchi Chen, Tao Gui +1
Multi-criteria Chinese word segmentation is a promising but challenging task, which exploits several different segmentation criteria and mines their common underlying knowledge. In…
Multi-task Learning over Graph Structures
Pengfei Liu, Jie Fu, Yue Dong +2
We present two architectures for multi-task learning with neural sequence models. Our approach allows the relationships between different tasks to be learned dynamically, rather th…
U-Net: Machine Reading Comprehension with Unanswerable Questions
Fu Sun, Linyang Li, Xipeng Qiu +1
Machine reading comprehension with unanswerable questions is a new challenging task for natural language processing. A key subtask is to reliably predict whether the question is un…
Deformable Stacked Structure for Named Entity Recognition
Shuyang Cao, Xipeng Qiu, Xuanjing Huang
Neural architecture for named entity recognition has achieved great success in the field of natural language processing. Currently, the dominating architecture consists of a bi-dir…
Neural Arithmetic Expression Calculator
Kaiyu Chen, Yihan Dong, Xipeng Qiu +1
This paper presents a pure neural solver for arithmetic expression calculation (AEC) problem. Previous work utilizes the powerful capabilities of deep neural networks and attempts…
Exploring Shared Structures and Hierarchies for Multiple NLP Tasks
Junkun Chen, Kaiyu Chen, Xinchi Chen +2
Designing shared neural architecture plays an important role in multi-task learning. The challenge is that finding an optimal sharing scheme heavily relies on the expert knowledge…
Top-Down Tree Structured Text Generation
Qipeng Guo, Xipeng Qiu, Xiangyang Xue +1
Text generation is a fundamental building block in natural language processing tasks. Existing sequential models performs autoregression directly over the text sequence and have di…
Information Aggregation via Dynamic Routing for Sequence Encoding
Jingjing Gong, Xipeng Qiu, Shaojing Wang +1
While much progress has been made in how to encode a text sequence into a sequence of vectors, less attention has been paid to how to aggregate these preceding vectors (outputs of…
Same Representation, Different Attentions: Shareable Sentence Representation Learning from Multiple Tasks
Renjie Zheng, Junkun Chen, Xipeng Qiu
Distributed representation plays an important role in deep learning based natural language processing. However, the representation of a sentence often varies in different tasks, wh…
Toward Diverse Text Generation with Inverse Reinforcement Learning
Zhan Shi, Xinchi Chen, Xipeng Qiu +1
Text generation is a crucial task in NLP. Recently, several adversarial generative models have been proposed to improve the exposure bias problem in text generation. Though these m…
Incorporating Discriminator in Sentence Generation: a Gibbs Sampling Method
Jinyue Su, Jiacheng Xu, Xipeng Qiu +1
Generating plausible and fluent sentence with desired properties has long been a challenge. Most of the recent works use recurrent neural networks (RNNs) and their variants to pred…
Meta Multi-Task Learning for Sequence Modeling
Junkun Chen, Xipeng Qiu, Pengfei Liu +1
Semantic composition functions have been playing a pivotal role in neural representation learning of text sequences. In spite of their success, most existing models suffer from the…