350 citations · 1.6k across the 83 of their papers we have counts for
17 papers · 1 filter
TENER: Adapting Transformer Encoder for Named Entity Recognition
Hang Yan, Bocao Deng, Xiaonan Li +1
The Bidirectional long short-term memory networks (BiLSTM) have been widely used as an encoder in models solving the named entity recognition (NER) task. Recently, the Transformer…
Multi-Scale Self-Attention for Text Classification
Qipeng Guo, Xipeng Qiu, Pengfei Liu +2
In this paper, we introduce the prior knowledge, multi-scale structure, into self-attention modules. We propose a Multi-Scale Transformer which uses multi-scale multi-head self-att…
Joint Parsing and Generation for Abstractive Summarization
Kaiqiang Song, Logan Lebanoff, Qipeng Guo +5
Sentences produced by abstractive summarization systems can be ungrammatical and fail to preserve the original meanings, despite being locally fluent. In this paper we propose to r…
Learning Sparse Sharing Architectures for Multiple Tasks
Tianxiang Sun, Yunfan Shao, Xiaonan Li +4
Most existing deep multi-task learning models are based on parameter sharing, such as hard sharing, hierarchical sharing, and soft sharing. How choosing a suitable sharing mechanis…
BP-Transformer: Modelling Long-Range Context via Binary Partitioning
Zihao Ye, Qipeng Guo, Quan Gan +2
The Transformer model is widely successful on many natural language processing tasks. However, the quadratic complexity of self-attention limit its application on long text. In thi…
A Closer Look at Data Bias in Neural Extractive Summarization Models
Ming Zhong, Danqing Wang, Pengfei Liu +2
In this paper, we take stock of the current state of summarization datasets and explore how different factors of datasets influence the generalization behaviour of neural extractiv…