306 citations · 1.3k across the 118 of their papers we have counts for
10 papers · 1 filter
Abstractive Text Summarization by Incorporating Reader Comments
Shen Gao, Xiuying Chen, Piji Li +4
In neural abstractive summarization field, conventional sequence-to-sequence based models often suffer from summarizing the wrong aspect of the document with respect to the main as…
A Unified Model for Opinion Target Extraction and Target Sentiment Prediction
Xin Li, Lidong Bing, Piji Li +1
Target-based sentiment analysis involves opinion target extraction and target sentiment classification. However, most of the existing works usually studied one of these two sub-tas…
Generating Distractors for Reading Comprehension Questions from Real Examinations
Yifan Gao, Lidong Bing, Piji Li +2
We investigate the task of distractor generation for multiple choice reading comprehension questions from examinations. In contrast to all previous works, we do not aim at preparin…
Difficulty Controllable Generation of Reading Comprehension Questions
Yifan Gao, Lidong Bing, Wang Chen +2
We investigate the difficulty levels of questions in reading comprehension datasets such as SQuAD, and propose a new question generation setting, named Difficulty-controllable Ques…
Semi-Supervised Learning with Declaratively Specified Entropy Constraints
Haitian Sun, William W. Cohen, Lidong Bing
We propose a technique for declaratively specifying strategies for semi-supervised learning (SSL). The proposed method can be used to specify ensembles of semi-supervised learning,…
Learning Domain-Sensitive and Sentiment-Aware Word Embeddings
Bei Shi, Zihao Fu, Lidong Bing +1
Word embeddings have been widely used in sentiment classification because of their efficacy for semantic representations of words. Given reviews from different domains, some existi…
Transformation Networks for Target-Oriented Sentiment Classification
Xin Li, Lidong Bing, Wai Lam +1
Target-oriented sentiment classification aims at classifying sentiment polarities over individual opinion targets in a sentence. RNN with attention seems a good fit for the charact…
Aspect Term Extraction with History Attention and Selective Transformation
Xin Li, Lidong Bing, Piji Li +2
Aspect Term Extraction (ATE), a key sub-task in Aspect-Based Sentiment Analysis, aims to extract explicit aspect expressions from online user reviews. We present a new framework fo…
QuaSE: Accurate Text Style Transfer under Quantifiable Guidance
Yi Liao, Lidong Bing, Piji Li +3
We propose the task of Quantifiable Sequence Editing (QuaSE): editing an input sequence to generate an output sequence that satisfies a given numerical outcome value measuring a ce…
Actor-Critic based Training Framework for Abstractive Summarization
Piji Li, Lidong Bing, Wai Lam
We present a training framework for neural abstractive summarization based on actor-critic approaches from reinforcement learning. In the traditional neural network based methods,…