Xiaolong Wang


2018

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LSDSCC: a Large Scale Domain-Specific Conversational Corpus for Response Generation with Diversity Oriented Evaluation Metrics
Zhen Xu | Nan Jiang | Bingquan Liu | Wenge Rong | Bowen Wu | Baoxun Wang | Zhuoran Wang | Xiaolong Wang
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)

It has been proven that automatic conversational agents can be built up using the Endto-End Neural Response Generation (NRG) framework, and such a data-driven methodology requires a large number of dialog pairs for model training and reasonable evaluation metrics for testing. This paper proposes a Large Scale Domain-Specific Conversational Corpus (LSDSCC) composed of high-quality queryresponse pairs extracted from the domainspecific online forum, with thorough preprocessing and cleansing procedures. Also, a testing set, including multiple diverse responses annotated for each query, is constructed, and on this basis, the metrics for measuring the diversity of generated results are further presented. We evaluate the performances of neural dialog models with the widely applied diversity boosting strategies on the proposed dataset. The experimental results have shown that our proposed corpus can be taken as a new benchmark dataset for the NRG task, and the presented metrics are promising to guide the optimization of NRG models by quantifying the diversity of the generated responses reasonably.

2017

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Predicting Users’ Negative Feedbacks in Multi-Turn Human-Computer Dialogues
Xin Wang | Jianan Wang | Yuanchao Liu | Xiaolong Wang | Zhuoran Wang | Baoxun Wang
Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

User experience is essential for human-computer dialogue systems. However, it is impractical to ask users to provide explicit feedbacks when the agents’ responses displease them. Therefore, in this paper, we explore to predict users’ imminent dissatisfactions caused by intelligent agents by analysing the existing utterances in the dialogue sessions. To our knowledge, this is the first work focusing on this task. Several possible factors that trigger negative emotions are modelled. A relation sequence model (RSM) is proposed to encode the sequence of appropriateness of current response with respect to the earlier utterances. The experimental results show that the proposed structure is effective in modelling emotional risk (possibility of negative feedback) than existing conversation modelling approaches. Besides, strategies of obtaining distance supervision data for pre-training are also discussed in this work. Balanced sampling with respect to the last response in the distance supervision data are shown to be reliable for data augmentation.

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Neural Response Generation via GAN with an Approximate Embedding Layer
Zhen Xu | Bingquan Liu | Baoxun Wang | Chengjie Sun | Xiaolong Wang | Zhuoran Wang | Chao Qi
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

This paper presents a Generative Adversarial Network (GAN) to model single-turn short-text conversations, which trains a sequence-to-sequence (Seq2Seq) network for response generation simultaneously with a discriminative classifier that measures the differences between human-produced responses and machine-generated ones. In addition, the proposed method introduces an approximate embedding layer to solve the non-differentiable problem caused by the sampling-based output decoding procedure in the Seq2Seq generative model. The GAN setup provides an effective way to avoid noninformative responses (a.k.a “safe responses”), which are frequently observed in traditional neural response generators. The experimental results show that the proposed approach significantly outperforms existing neural response generation models in diversity metrics, with slight increases in relevance scores as well, when evaluated on both a Mandarin corpus and an English corpus.

2016

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Incorporating Label Dependency for Answer Quality Tagging in Community Question Answering via CNN-LSTM-CRF
Yang Xiang | Xiaoqiang Zhou | Qingcai Chen | Zhihui Zheng | Buzhou Tang | Xiaolong Wang | Yang Qin
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers

In community question answering (cQA), the quality of answers are determined by the matching degree between question-answer pairs and the correlation among the answers. In this paper, we show that the dependency between the answer quality labels also plays a pivotal role. To validate the effectiveness of label dependency, we propose two neural network-based models, with different combination modes of Convolutional Neural Net-works, Long Short Term Memory and Conditional Random Fields. Extensive experi-ments are taken on the dataset released by the SemEval-2015 cQA shared task. The first model is a stacked ensemble of the networks. It achieves 58.96% on macro averaged F1, which improves the state-of-the-art neural network-based method by 2.82% and outper-forms the Top-1 system in the shared task by 1.77%. The second is a simple attention-based model whose input is the connection of the question and its corresponding answers. It produces promising results with 58.29% on overall F1 and gains the best performance on the Good and Bad categories.

2015

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Predicting Polarities of Tweets by Composing Word Embeddings with Long Short-Term Memory
Xin Wang | Yuanchao Liu | Chengjie Sun | Baoxun Wang | Xiaolong Wang
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

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Answer Sequence Learning with Neural Networks for Answer Selection in Community Question Answering
Xiaoqiang Zhou | Baotian Hu | Qingcai Chen | Buzhou Tang | Xiaolong Wang
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)

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Chinese Grammatical Error Diagnosis Using Ensemble Learning
Yang Xiang | Xiaolong Wang | Wenying Han | Qinghua Hong
Proceedings of the 2nd Workshop on Natural Language Processing Techniques for Educational Applications

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yiGou: A Semantic Text Similarity Computing System Based on SVM
Yang Liu | Chengjie Sun | Lei Lin | Xiaolong Wang
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)

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HITSZ-ICRC: Exploiting Classification Approach for Answer Selection in Community Question Answering
Yongshuai Hou | Cong Tan | Xiaolong Wang | Yaoyun Zhang | Jun Xu | Qingcai Chen
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)

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ICRC-HIT: A Deep Learning based Comment Sequence Labeling System for Answer Selection Challenge
Xiaoqiang Zhou | Baotian Hu | Jiaxin Lin | Yang Xiang | Xiaolong Wang
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)

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HITSZ-ICRC: An Integration Approach for QA TempEval Challenge
Yongshuai Hou | Cong Tan | Qingcai Chen | Xiaolong Wang
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)

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Computing Semantic Text Similarity Using Rich Features
Yang Liu | Chengjie Sun | Lei Lin | Xiaolong Wang | Yuming Zhao
Proceedings of the 29th Pacific Asia Conference on Language, Information and Computation

2014

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Cross-lingual Opinion Analysis via Negative Transfer Detection
Lin Gui | Ruifeng Xu | Qin Lu | Jun Xu | Jian Xu | Bin Liu | Xiaolong Wang
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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WINGS:Writing with Intelligent Guidance and Suggestions
Xianjun Dai | Yuanchao Liu | Xiaolong Wang | Bingquan Liu
Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations

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Problematic Situation Analysis and Automatic Recognition for Chinese Online Conversational System
Yang Xiang | Yaoyun Zhang | Xiaoqiang Zhou | Xiaolong Wang | Yang Qin
Proceedings of The Third CIPS-SIGHAN Joint Conference on Chinese Language Processing

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Identification of Basic Phrases for Kazakh Language using Maximum Entropy Model
Gulila Altenbek | Xiaolong Wang | Gulizhada Haisha
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers

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Hybrid Deep Belief Networks for Semi-supervised Sentiment Classification
Shusen Zhou | Qingcai Chen | Xiaolong Wang | Xiaoling Li
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers

2013

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Multimodal DBN for Predicting High-Quality Answers in cQA portals
Haifeng Hu | Bingquan Liu | Baoxun Wang | Ming Liu | Xiaolong Wang
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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PAL: A Chatterbot System for Answering Domain-specific Questions
Yuanchao Liu | Ming Liu | Xiaolong Wang | Limin Wang | Jingjing Li
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics: System Demonstrations

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Automatic Corpora Construction for Text Classification
Dandan Wang | Qingcai Chen | Xiaolong Wang | Bingyang Yu
Proceedings of the Sixth International Joint Conference on Natural Language Processing

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Grammatical Error Correction Using Feature Selection and Confidence Tuning
Yang Xiang | Yaoyun Zhang | Xiaolong Wang | Chongqiang Wei | Wen Zheng | Xiaoqiang Zhou | Yuxiu Hu | Yang Qin
Proceedings of the Sixth International Joint Conference on Natural Language Processing

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A Hybrid Model For Grammatical Error Correction
Yang Xiang | Bo Yuan | Yaoyun Zhang | Xiaolong Wang | Wen Zheng | Chongqiang Wei
Proceedings of the Seventeenth Conference on Computational Natural Language Learning: Shared Task

2012

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A Mixed Deterministic Model for Coreference Resolution
Bo Yuan | Qingcai Chen | Yang Xiang | Xiaolong Wang | Liping Ge | Zengjian Liu | Meng Liao | Xianbo Si
Joint Conference on EMNLP and CoNLL - Shared Task

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Generating Questions from Web Community Contents
Baoxun Wang | Bingquan Liu | Chengjie Sun | Xiaolong Wang | Deyuan Zhang
Proceedings of COLING 2012: Demonstration Papers

2011

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Diversifying Information Needs in Results of Question Retrieval
Yaoyun Zhang | Xiaolong Wang | Xuan Wang | Ruifeng Xu | Jun Xu | ShiXi Fan
Proceedings of 5th International Joint Conference on Natural Language Processing

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Instance Level Transfer Learning for Cross Lingual Opinion Analysis
Ruifeng Xu | Jun Xu | Xiaolong Wang
Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis (WASSA 2.011)

2010

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Modeling Semantic Relevance for Question-Answer Pairs in Web Social Communities
Baoxun Wang | Xiaolong Wang | Chengjie Sun | Bingquan Liu | Lin Sun
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

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A Cascade Method for Detecting Hedges and their Scope in Natural Language Text
Buzhou Tang | Xiaolong Wang | Xuan Wang | Bo Yuan | Shixi Fan
Proceedings of the Fourteenth Conference on Computational Natural Language Learning – Shared Task

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Active Deep Networks for Semi-Supervised Sentiment Classification
Shusen Zhou | Qingcai Chen | Xiaolong Wang
Coling 2010: Posters

2009

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A Joint Syntactic and Semantic Dependency Parsing System based on Maximum Entropy Models
Buzhou Tang | Lu Li | Xinxin Li | Xuan Wang | Xiaolong Wang
Proceedings of the Thirteenth Conference on Computational Natural Language Learning (CoNLL 2009): Shared Task

2008

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Chunking with Max-Margin Markov Networks
Buzhou Tang | Xuan Wang | Xiaolong Wang
Proceedings of the 22nd Pacific Asia Conference on Language, Information and Computation

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Semantic Chunk Annotation for complex questions using Conditional Random Field
Shixi Fan | Yaoyun Zhang | Wing W. Y. Ng | Xuan Wang | Xiaolong Wang
Coling 2008: Proceedings of the workshop on Knowledge and Reasoning for Answering Questions

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Discriminative Learning of Syntactic and Semantic Dependencies
Lu Li | Shixi Fan | Xuan Wang | Xiaolong Wang
CoNLL 2008: Proceedings of the Twelfth Conference on Computational Natural Language Learning

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Name Origin Recognition Using Maximum Entropy Model and Diverse Features
Min Zhang | Chengjie Sun | Haizhou Li | AiTi Aw | Chew Lim Tan | Xiaolong Wang
Proceedings of the Third International Joint Conference on Natural Language Processing: Volume-I

2007

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An Empirical Study of Non-Stationary Ngram Model and its Smoothing Techniques
Jinghui Xiao | Bingquan Liu | Xiaolong Wang
International Journal of Computational Linguistics & Chinese Language Processing, Volume 12, Number 2, June 2007

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Exploiting Pinyin Constraints in Pinyin-to-Character Conversion Task: a Class-Based Maximum Entropy Markov Model Approach
Jinghui Xiao | Bingquan Liu | Xiaolong Wang
International Journal of Computational Linguistics & Chinese Language Processing, Volume 12, Number 3, September 2007: Special Issue on Invited Papers from ISCSLP 2006

2005

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Detecting Segmentation Errors in Chinese Annotated Corpus
Chengjie Sun | Chang-Ning Huang | Xiaolong Wang | Mu Li
Proceedings of the Fourth SIGHAN Workshop on Chinese Language Processing