Sheng Li


2021

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Proceedings of the 20th Chinese National Conference on Computational Linguistics
Sheng Li (李生) | Maosong Sun (孙茂松) | Yang Liu (刘洋) | Hua Wu (吴华) | Kang Liu (刘康) | Wanxiang Che (车万翔) | Shizhu He (何世柱) | Gaoqi Rao (饶高琦)
Proceedings of the 20th Chinese National Conference on Computational Linguistics

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Edge: Enriching Knowledge Graph Embeddings with External Text
Saed Rezayi | Handong Zhao | Sungchul Kim | Ryan Rossi | Nedim Lipka | Sheng Li
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Knowledge graphs suffer from sparsity which degrades the quality of representations generated by various methods. While there is an abundance of textual information throughout the web and many existing knowledge bases, aligning information across these diverse data sources remains a challenge in the literature. Previous work has partially addressed this issue by enriching knowledge graph entities based on “hard” co-occurrence of words present in the entities of the knowledge graphs and external text, while we achieve “soft” augmentation by proposing a knowledge graph enrichment and embedding framework named Edge. Given an original knowledge graph, we first generate a rich but noisy augmented graph using external texts in semantic and structural level. To distill the relevant knowledge and suppress the introduced noise, we design a graph alignment term in a shared embedding space between the original graph and augmented graph. To enhance the embedding learning on the augmented graph, we further regularize the locality relationship of target entity based on negative sampling. Experimental results on four benchmark datasets demonstrate the robustness and effectiveness of Edge in link prediction and node classification.

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Exploiting Auxiliary Data for Offensive Language Detection with Bidirectional Transformers
Sumer Singh | Sheng Li
Proceedings of the 5th Workshop on Online Abuse and Harms (WOAH 2021)

Offensive language detection (OLD) has received increasing attention due to its societal impact. Recent work shows that bidirectional transformer based methods obtain impressive performance on OLD. However, such methods usually rely on large-scale well-labeled OLD datasets for model training. To address the issue of data/label scarcity in OLD, in this paper, we propose a simple yet effective domain adaptation approach to train bidirectional transformers. Our approach introduces domain adaptation (DA) training procedures to ALBERT, such that it can effectively exploit auxiliary data from source domains to improve the OLD performance in a target domain. Experimental results on benchmark datasets show that our approach, ALBERT (DA), obtains the state-of-the-art performance in most cases. Particularly, our approach significantly benefits underrepresented and under-performing classes, with a significant improvement over ALBERT.

2020

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CAN-GRU: a Hierarchical Model for Emotion Recognition in Dialogue
Ting Jiang | Bing Xu | Tiejun Zhao | Sheng Li
Proceedings of the 19th Chinese National Conference on Computational Linguistics

Emotion recognition in dialogue systems has gained attention in the field of natural language processing recent years, because it can be applied in opinion mining from public conversational data on social media. In this paper, we propose a hierarchical model to recognize emotions in the dialogue. In the first layer, in order to extract textual features of utterances, we propose a convolutional self-attention network(CAN). Convolution is used to capture n-gram information and attention mechanism is used to obtain the relevant semantic information among words in the utterance. In the second layer, a GRU-based network helps to capture contextual information in the conversation. Furthermore, we discuss the effects of unidirectional and bidirectional networks. We conduct experiments on Friends dataset and EmotionPush dataset. The results show that our proposed model(CAN-GRU) and its variants achieve better performance than baselines.

2018

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A Review on Deep Learning Techniques Applied to Answer Selection
Tuan Manh Lai | Trung Bui | Sheng Li
Proceedings of the 27th International Conference on Computational Linguistics

Given a question and a set of candidate answers, answer selection is the task of identifying which of the candidates answers the question correctly. It is an important problem in natural language processing, with applications in many areas. Recently, many deep learning based methods have been proposed for the task. They produce impressive performance without relying on any feature engineering or expensive external resources. In this paper, we aim to provide a comprehensive review on deep learning methods applied to answer selection.

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Supervised Treebank Conversion: Data and Approaches
Xinzhou Jiang | Zhenghua Li | Bo Zhang | Min Zhang | Sheng Li | Luo Si
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Treebank conversion is a straightforward and effective way to exploit various heterogeneous treebanks for boosting parsing performance. However, previous work mainly focuses on unsupervised treebank conversion and has made little progress due to the lack of manually labeled data where each sentence has two syntactic trees complying with two different guidelines at the same time, referred as bi-tree aligned data. In this work, we for the first time propose the task of supervised treebank conversion. First, we manually construct a bi-tree aligned dataset containing over ten thousand sentences. Then, we propose two simple yet effective conversion approaches (pattern embedding and treeLSTM) based on the state-of-the-art deep biaffine parser. Experimental results show that 1) the two conversion approaches achieve comparable conversion accuracy, and 2) treebank conversion is superior to the widely used multi-task learning framework in multi-treebank exploitation and leads to significantly higher parsing accuracy.

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A Simple End-to-End Question Answering Model for Product Information
Tuan Lai | Trung Bui | Sheng Li | Nedim Lipka
Proceedings of the First Workshop on Economics and Natural Language Processing

When evaluating a potential product purchase, customers may have many questions in mind. They want to get adequate information to determine whether the product of interest is worth their money. In this paper we present a simple deep learning model for answering questions regarding product facts and specifications. Given a question and a product specification, the model outputs a score indicating their relevance. To train and evaluate our proposed model, we collected a dataset of 7,119 questions that are related to 153 different products. Experimental results demonstrate that –despite its simplicity– the performance of our model is shown to be comparable to a more complex state-of-the-art baseline.

2016

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SoNLP-DP System for ConLL-2016 English Shallow Discourse Parsing
Fang Kong | Sheng Li | Junhui Li | Muhua Zhu | Guodong Zhou
Proceedings of the CoNLL-16 shared task

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SoNLP-DP System for ConLL-2016 Chinese Shallow Discourse Parsing
Junhui Li | Fang Kong | Sheng Li | Muhua Zhu | Guodong Zhou
Proceedings of the CoNLL-16 shared task

2015

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Hierarchical Recurrent Neural Network for Document Modeling
Rui Lin | Shujie Liu | Muyun Yang | Mu Li | Ming Zhou | Sheng Li
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

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Lifetime Achievement Award: Translating Today into Tomorrow
Sheng Li
Computational Linguistics, Volume 41, Issue 4 - December 2015

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The SoNLP-DP System in the CoNLL-2015 shared Task
Fang Kong | Sheng Li | Guodong Zhou
Proceedings of the Nineteenth Conference on Computational Natural Language Learning - Shared Task

2014

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Detection on Inconsistency of Verb Phrase in TreeBank
Chaoqun Duan | Dequan Zheng | Conghui Zhu | Sheng Li | Hongye Tan
Proceedings of The Third CIPS-SIGHAN Joint Conference on Chinese Language Processing

2013

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Microblog Entity Linking by Leveraging Extra Posts
Yuhang Guo | Bing Qin | Ting Liu | Sheng Li
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

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A Hierarchical Semantics-Aware Distributional Similarity Scheme
Shuqi Sun | Ke Sun | Shiqi Zhao | Haifeng Wang | Muyun Yang | Sheng Li
Proceedings of the Sixth International Joint Conference on Natural Language Processing

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Repairing Incorrect Translation with Examples
Junguo Zhu | Muyun Yang | Sheng Li | Tiejun Zhao
Proceedings of the Sixth International Joint Conference on Natural Language Processing

2011

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A Graph-based Method for Entity Linking
Yuhang Guo | Wanxiang Che | Ting Liu | Sheng Li
Proceedings of 5th International Joint Conference on Natural Language Processing

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Harvesting Related Entities with a Search Engine
Shuqi Sun | Shiqi Zhao | Muyun Yang | Haifeng Wang | Sheng Li
Proceedings of 5th International Joint Conference on Natural Language Processing

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Hypergraph Training and Decoding of System Combination in SMT
Yupeng Liu | Tiejun Zhao | Sheng Li
Proceedings of Machine Translation Summit XIII: Papers

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Reordering with Source Language Collocations
Zhanyi Liu | Haifeng Wang | Hua Wu | Ting Liu | Sheng Li
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

2010

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HIT-CIR: An Unsupervised WSD System Based on Domain Most Frequent Sense Estimation
Yuhang Guo | Wanxiang Che | Wei He | Ting Liu | Sheng Li
Proceedings of the 5th International Workshop on Semantic Evaluation

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Selecting Optimal Feature Template Subset for CRFs
Xingjun Xu | Guanglu Sun | Yi Guan | Xishuang Dong | Sheng Li
CIPS-SIGHAN Joint Conference on Chinese Language Processing

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Complete Syntactic Analysis Bases on Multi-level Chunking
Zhipeng Jiang | Yu Zhao | Yi Guan | Chao Li | Sheng Li
CIPS-SIGHAN Joint Conference on Chinese Language Processing

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Improving Statistical Machine Translation with Monolingual Collocation
Zhanyi Liu | Haifeng Wang | Hua Wu | Sheng Li
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

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Reexamination on Potential for Personalization in Web Search
Daren Li | Muyun Yang | HaoLiang Qi | Sheng Li | Tiejun Zhao
Coling 2010: Posters

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Head-modifier Relation based Non-lexical Reordering Model for Phrase-Based Translation
Shui Liu | Sheng Li | Tiejun Zhao | Min Zhang | Pengyuan Liu
Coling 2010: Posters

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Bridging Topic Modeling and Personalized Search
Wei Song | Yu Zhang | Ting Liu | Sheng Li
Coling 2010: Posters

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Utilizing Variability of Time and Term Content, within and across Users in Session Detection
Shuqi Sun | Sheng Li | Muyun Yang | Haoliang Qi | Tiejun Zhao
Coling 2010: Posters

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All in Strings: a Powerful String-based Automatic MT Evaluation Metric with Multiple Granularities
Junguo Zhu | Muyun Yang | Bo Wang | Sheng Li | Tiejun Zhao
Coling 2010: Posters

2009

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Application-driven Statistical Paraphrase Generation
Shiqi Zhao | Xiang Lan | Ting Liu | Sheng Li
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP

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A Statistical Machine Translation Model Based on a Synthetic Synchronous Grammar
Hongfei Jiang | Muyun Yang | Tiejun Zhao | Sheng Li | Bo Wang
Proceedings of the ACL-IJCNLP 2009 Conference Short Papers

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Collocation Extraction Using Monolingual Word Alignment Method
Zhanyi Liu | Haifeng Wang | Hua Wu | Sheng Li
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing

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References Extension for the Automatic Evaluation of MT by Syntactic Hybridization
Bo Wang | Tiejun Zhao | Muyun Yang | Sheng Li
Proceedings of the Third Workshop on Syntax and Structure in Statistical Translation (SSST-3) at NAACL HLT 2009

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A Study of Translation Rule Classification for Syntax-based Statistical Machine Translation
Hongfei Jiang | Sheng Li | Muyun Yang | Tiejun Zhao
Proceedings of the Third Workshop on Syntax and Structure in Statistical Translation (SSST-3) at NAACL HLT 2009

2008

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A Cascaded Syntactic and Semantic Dependency Parsing System
Wanxiang Che | Zhenghua Li | Yuxuan Hu | Yongqiang Li | Bing Qin | Ting Liu | Sheng Li
CoNLL 2008: Proceedings of the Twelfth Conference on Computational Natural Language Learning

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Grammar Comparison Study for Translational Equivalence Modeling and Statistical Machine Translation
Min Zhang | Hongfei Jiang | Haizhou Li | Aiti Aw | Sheng Li
Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008)

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Fast Computing Grammar-driven Convolution Tree Kernel for Semantic Role Labeling
Wanxiang Che | Min Zhang | Ai Ti Aw | Chew Lim Tan | Ting Liu | Sheng Li
Proceedings of the Third International Joint Conference on Natural Language Processing: Volume-II

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A Tree Sequence Alignment-based Tree-to-Tree Translation Model
Min Zhang | Hongfei Jiang | Aiti Aw | Haizhou Li | Chew Lim Tan | Sheng Li
Proceedings of ACL-08: HLT

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Pivot Approach for Extracting Paraphrase Patterns from Bilingual Corpora
Shiqi Zhao | Haifeng Wang | Ting Liu | Sheng Li
Proceedings of ACL-08: HLT

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An Entity-Mention Model for Coreference Resolution with Inductive Logic Programming
Xiaofeng Yang | Jian Su | Jun Lang | Chew Lim Tan | Ting Liu | Sheng Li
Proceedings of ACL-08: HLT

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Combining Multiple Resources to Improve SMT-based Paraphrasing Model
Shiqi Zhao | Cheng Niu | Ming Zhou | Ting Liu | Sheng Li
Proceedings of ACL-08: HLT

2007

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The Extraction of Trajectories from Real Texts Based on Linear Classification
Hanjing Li | Tiejun Zhao | Sheng Li | Jiyuan Zhao
Proceedings of the 16th Nordic Conference of Computational Linguistics (NODALIDA 2007)

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HIT: Web based Scoring Method for English Lexical Substitution
Shiqi Zhao | Lin Zhao | Yu Zhang | Ting Liu | Sheng Li
Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007)

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A tree-to-tree alignment-based model for statistical machine translation
Min Zhang | Hongfei Jiang | Ai Ti Aw | Jun Sun | Sheng Li | Chew Lim Tan
Proceedings of Machine Translation Summit XI: Papers

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A Grammar-driven Convolution Tree Kernel for Semantic Role Classification
Min Zhang | Wanxiang Che | Aiti Aw | Chew Lim Tan | Guodong Zhou | Ting Liu | Sheng Li
Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics

2006

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An Equivalent Pseudoword Solution to Chinese Word Sense Disambiguation
Zhimao Lu | Haifeng Wang | Jianmin Yao | Ting Liu | Sheng Li
Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics

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A Hybrid Convolution Tree Kernel for Semantic Role Labeling
Wanxiang Che | Min Zhang | Ting Liu | Sheng Li
Proceedings of the COLING/ACL 2006 Main Conference Poster Sessions

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Dependency Parsing Based on Dynamic Local Optimization
Ting Liu | Jinshan Ma | Huijia Zhu | Sheng Li
Proceedings of the Tenth Conference on Computational Natural Language Learning (CoNLL-X)

2005

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Semantic Role Labeling System Using Maximum Entropy Classifier
Ting Liu | Wanxiang Che | Sheng Li | Yuxuan Hu | Huaijun Liu
Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL-2005)

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A Hybrid Chinese Language Model based on a Combination of Ontology with Statistical Method
Dequan Zheng | Tiejun Zhao | Sheng Li | Hao Yu
Companion Volume to the Proceedings of Conference including Posters/Demos and tutorial abstracts

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Automated Generalization of Phrasal Paraphrases from the Web
Weigang Li | Ting Liu | Yu Zhang | Sheng Li | Wei He
Proceedings of the Third International Workshop on Paraphrasing (IWP2005)

2004

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Combining Neural Networks and Statistics for Chinese Word Sense Disambiguation
Zhimao Lu | Ting Liu | Sheng Li
Proceedings of the Third SIGHAN Workshop on Chinese Language Processing

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A New Chinese Natural Language Understanding Architecture Based on Multilayer Search Mechanism
Wanxiang Che | Ting Liu | Sheng Li
Proceedings of the Third SIGHAN Workshop on Chinese Language Processing

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Aligning Bilingual Corpora Using Sentences Location Information
Weigang Li | Ting Liu | Zhen Wang | Sheng Li
Proceedings of the Third SIGHAN Workshop on Chinese Language Processing

2002

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Learning Chinese Bracketing Knowledge Based on a Bilingual Language Model
Yajuan Lü | Sheng Li | Tiejun Zhao | Muyun Yang
COLING 2002: The 19th International Conference on Computational Linguistics

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An Automatic Evaluation Method for Localization Oriented Lexicalised EBMT System
Jianmin Yao | Ming Zhou | Tiejun Zhao | Hao Yu | Sheng Li
COLING 2002: The 19th International Conference on Computational Linguistics

2001

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Automatic Translation Template Acquisition Based on Bilingual Structure Alignment
Yajuan Lu | Ming Zhou | Sheng Li | Changning Huang | Tiejun Zhao
International Journal of Computational Linguistics & Chinese Language Processing, Volume 6, Number 1, February 2001: Special Issue on Natural Language Processing Researches in MSRA