402 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Alibaba Group (China)CN60 papers
- Zhejiang UniversityCN46 papers
- Bellevue Hospital CenterUS30 papers
- Peking UniversityCN22 papers
- Nanyang Technological UniversitySG21 papers
- Tsinghua UniversityCN15 papers
- Chinese Academy of SciencesCN14 papers
- Renmin University of ChinaCN13 papers
- Shanghai Jiao Tong UniversityCN11 papers
- Tianjin UniversityCN11 papers
- Alibaba Group (Cayman Islands)KY10 papers
- East China Normal UniversityCN10 papers
19 papers · 2 filters
Acquiring Knowledge from Pre-trained Model to Neural Machine Translation
Rongxiang Weng, Heng Yu, Shujian Huang +2
Pre-training and fine-tuning have achieved great success in the natural language process field. The standard paradigm of exploiting them includes two steps: first, pre-training a m…
Improving Neural Relation Extraction with Positive and Unlabeled Learning
Zhengqiu He, Wenliang Chen, Yuyi Wang +3
We present a novel approach to improve the performance of distant supervision relation extraction with Positive and Unlabeled (PU) Learning. This approach first applies reinforceme…
Independent language modeling architecture for end-to-end ASR
Van Tung Pham, Haihua Xu, Yerbolat Khassanov +5
The attention-based end-to-end (E2E) automatic speech recognition (ASR) architecture allows for joint optimization of acoustic and language models within a single network. However,…
Joint Learning of Answer Selection and Answer Summary Generation in Community Question Answering
Yang Deng, Wai Lam, Yuexiang Xie +4
Community question answering (CQA) gains increasing popularity in both academy and industry recently. However, the redundancy and lengthiness issues of crowdsourced answers limit t…
Knowing What, How and Why: A Near Complete Solution for Aspect-based Sentiment Analysis
Haiyun Peng, Lu Xu, Lidong Bing +3
Target-based sentiment analysis or aspect-based sentiment analysis (ABSA) refers to addressing various sentiment analysis tasks at a fine-grained level, which includes but is not l…
Contrastive Attention Mechanism for Abstractive Sentence Summarization
Xiangyu Duan, Hoongfei Yu, Mingming Yin +3
We propose a contrastive attention mechanism to extend the sequence-to-sequence framework for abstractive sentence summarization task, which aims to generate a brief summary of a g…
Syntax-Enhanced Self-Attention-Based Semantic Role Labeling
Yue Zhang, Rui Wang, Luo Si
As a fundamental NLP task, semantic role labeling (SRL) aims to discover the semantic roles for each predicate within one sentence. This paper investigates how to incorporate synta…
Low-Resource Sequence Labeling via Unsupervised Multilingual Contextualized Representations
Zuyi Bao, Rui Huang, Chen Li +1
Previous work on cross-lingual sequence labeling tasks either requires parallel data or bridges the two languages through word-byword matching. Such requirements and assumptions ar…
StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding
Wei Wang, Bin Bi, Ming Yan +5
Recently, the pre-trained language model, BERT (and its robustly optimized version RoBERTa), has attracted a lot of attention in natural language understanding (NLU), and achieved…
Task-Oriented Conversation Generation Using Heterogeneous Memory Networks
Zehao Lin, Xinjing Huang, Feng Ji +2
How to incorporate external knowledge into a neural dialogue model is critically important for dialogue systems to behave like real humans. To handle this problem, memory networks…
Syntax-aware Neural Semantic Role Labeling
Qingrong Xia, Zhenghua Li, Min Zhang +4
Semantic role labeling (SRL), also known as shallow semantic parsing, is an important yet challenging task in NLP. Motivated by the close correlation between syntactic and semantic…
Sequence Generation: From Both Sides to the Middle
Long Zhou, Jiajun Zhang, Chengqing Zong +1
The encoder-decoder framework has achieved promising process for many sequence generation tasks, such as neural machine translation and text summarization. Such a framework usually…
Multi-Grained Named Entity Recognition
Congying Xia, Chenwei Zhang, Tao Yang +6
This paper presents a novel framework, MGNER, for Multi-Grained Named Entity Recognition where multiple entities or entity mentions in a sentence could be non-overlapping or totall…
Lattice Transformer for Speech Translation
Pei Zhang, Boxing Chen, Niyu Ge +1
Recent advances in sequence modeling have highlighted the strengths of the transformer architecture, especially in achieving state-of-the-art machine translation results. However,…
BiSET: Bi-directional Selective Encoding with Template for Abstractive Summarization
Kai Wang, Xiaojun Quan, Rui Wang
The success of neural summarization models stems from the meticulous encodings of source articles. To overcome the impediments of limited and sometimes noisy training data, one pro…
Automated Curriculum Learning for Turn-level Spoken Language Understanding with Weak Supervision
Hao Lang, Wen Wang
We propose a learning approach for turn-level spoken language understanding, which facilitates a user to speak one or more utterances compositionally in a turn for completing a tas…
Cognitive Graph for Multi-Hop Reading Comprehension at Scale
Ming Ding, Chang Zhou, Qibin Chen +2
We propose a new CogQA framework for multi-hop question answering in web-scale documents. Inspired by the dual process theory in cognitive science, the framework gradually builds a…
Enriching Pre-trained Language Model with Entity Information for Relation Classification
Shanchan Wu, Yifan He
Relation classification is an important NLP task to extract relations between entities. The state-of-the-art methods for relation classification are primarily based on Convolutiona…
Multi-Modal Generative Adversarial Network for Short Product Title Generation in Mobile E-Commerce
Jian-Guo Zhang, Pengcheng Zou, Zhao Li +4
Nowadays, more and more customers browse and purchase products in favor of using mobile E-Commerce Apps such as Taobao and Amazon. Since merchants are usually inclined to describe…