Nan Yang

Publications
Influence

Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification

Duyu Tang, Furu Wei, Nan Yang, M. Zhou, T. Liu, Bing Qin
Computer Science
ACL
1 June 2014

We present a method that learns word embedding for Twitter sentiment classification in this paper, which encodes sentiment information in the continuous representation of words. Expand

Gated Self-Matching Networks for Reading Comprehension and Question Answering

Wenhui Wang, Nan Yang, Furu Wei, Baobao Chang, M. Zhou
Computer Science
ACL
1 July 2017

In this paper, we present the gated self-matching networks for reading comprehension style question answering which aims to answer questions from a given passage. Expand

Unified Language Model Pre-training for Natural Language Understanding and Generation

Li Dong, Nan Yang, +6 authors H. Hon
Computer Science
NeurIPS
8 May 2019

This paper presents a new Unified pre-trained Language Model (UniLM) that can be fine-tuned for both natural language understanding and generation tasks. Expand

Neural Question Generation from Text: A Preliminary Study

Qingyu Zhou, Nan Yang, Furu Wei, Chuanqi Tan, Hangbo Bao, M. Zhou
Computer Science
NLPCC
6 April 2017

We propose to apply neural encoder-decoder model to generate answer focused questions based on natural language sentences. Expand

Selective Encoding for Abstractive Sentence Summarization

Qingyu Zhou, Nan Yang, Furu Wei, M. Zhou
Computer Science
ACL
1 April 2017

We propose a selective encoding model to extend the sequence-to-sequence framework for abstractive sentence summarization. Expand

Neural Document Summarization by Jointly Learning to Score and Select Sentences

Qingyu Zhou, Nan Yang, Furu Wei, Shaohan Huang, M. Zhou, T. Zhao
Computer Science
ACL
1 July 2018

We present a novel end-to-end neural network framework for extractive document summarization by jointly learning to score and select sentences. Expand

Sentiment Embeddings with Applications to Sentiment Analysis

Duyu Tang, Furu Wei, Bing Qin, Nan Yang, T. Liu, M. Zhou
Computer Science
IEEE Transactions on Knowledge and Data…
1 February 2016

We propose learning sentiment-specific word embeddings dubbed sentiment embedDings in this paper. Expand

Read + Verify: Machine Reading Comprehension with Unanswerable Questions

Minghao Hu, Furu Wei, Yu-xing Peng, Z. Huang, Nan Yang, M. Zhou
Computer Science
AAAI
17 August 2018

We propose a novel read-then-verify system that not only utilizes a neural reader to extract candidate answers and produce no-answer probabilities, but also leverages an answer verifier to decide whether the predicted answer is entailed by the input snippets. Expand

Modeling Mention, Context and Entity with Neural Networks for Entity Disambiguation

Yaming Sun, Lei Lin, Duyu Tang, Nan Yang, Zhenzhou Ji, Xiaolong Wang
Computer Science
IJCAI
25 July 2015

We model variable-sized contexts with convolutional neural network, and embed the positions of context words to factor in the distance between context word and mention. Expand

Sequence-to-Dependency Neural Machine Translation

Shuangzhi Wu, Dongdong Zhang, Nan Yang, Mu Li, M. Zhou
Computer Science
ACL
1 July 2017

We propose a novel Sequence-to-Dependency Neural Machine Translation (SD-NMT) method, in which the target word sequence and its corresponding dependency structure are jointly constructed and modeled, and this structure is used as context to facilitate word generations. Expand

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