Xipeng Qiu

Professor, School of Computer Science, Fudan University

 

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Computer Building, No. 825, Zhangheng Road, Shanghai, China

    A more comprehensive publication list: Google Scholar

    [2020]

  1. A Graph-based Model for Joint Chinese Word Segmentation and Dependency Parsing, Transactions of the Association for Computational Linguistics (TACL) , Vol. 8, pp. 78-92, 2020. [BibTeX][DOI][PDF]
    Hang Yan, Xipeng Qiu, Xuanjing Huang.
  2. BibTeX:
    @article{yan2020graph,
      author = {Yan, Hang and Qiu, Xipeng and Huang, Xuanjing},
      title = {A Graph-based Model for Joint Chinese Word Segmentation and Dependency Parsing},
      journal = {Transactions of the Association for Computational Linguistics},
      year = {2020},
      volume = {8},
      pages = {78--92},
      doi = {https://doi.org/10.1162/tacl_a_00301}
    }
    
  3. FLAT: Chinese NER Using Flat-Lattice Transformer, ACL, 2020. [BibTeX][PDF][Code]
    Abstract: Recently, the character-word lattice structure has been proved to be effective for Chinese named entity recognition (NER) by incorporating the word information. However, since the lattice structure is complex and dynamic, the lattice-based models are hard to fully utilize the parallel computation of GPUs and usually have a low inference speed. In this paper, we propose FLAT: Flat-LAttice Transformer for Chinese NER, which converts the lattice structure into a flat structure consisting of spans. Each span corresponds to a character or latent word and its position in the original lattice. With the power of Transformer and well-designed position encoding, FLAT can fully leverage the lattice information and has an excellent parallel ability. Experiments on four datasets show FLAT outperforms other lexicon-based models in performance and efficiency.
    Xiaonan Li, Hang Yan, Xipeng Qiu, Xuanjing Huang.
    [Abstract]
  4. BibTeX:
    @inproceedings{li-etal-2020-flat,
      author = {Li, Xiaonan and Yan, Hang and Qiu, Xipeng and Huang, Xuanjing},
      title = {FLAT: Chinese NER Using Flat-Lattice Transformer},
      booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
      year = {2020},
      pages = {6836--6842}, 
      url = {https://www.aclweb.org/anthology/2020.acl-main.611}
    }
    
  5. Improving Image Captioning with Better Use of Caption, ACL, 2020. [BibTeX][PDF][Code]
    Abstract: Image captioning is a multimodal problem that has drawn extensive attention in both the natural language processing and computer vision community. In this paper, we present a novel image captioning architecture to better explore semantics available in captions and leverage that to enhance both image representation and caption generation. Our models first construct caption-guided visual relationship graphs that introduce beneficial inductive bias using weakly supervised multi-instance learning. The representation is then enhanced with neighbouring and contextual nodes with their textual and visual features. During generation, the model further incorporates visual relationships using multi-task learning for jointly predicting word and object/predicate tag sequences. We perform extensive experiments on the MSCOCO dataset, showing that the proposed framework significantly outperforms the baselines, resulting in the state-of-the-art performance under a wide range of evaluation metrics. The code of our paper has been made publicly available.
    Zhan Shi, Xu Zhou, Xipeng Qiu, Xiaodan Zhu.
    [Abstract]
  6. BibTeX:
    @inproceedings{shi-etal-2020-improving,
      author = {Shi, Zhan and Zhou, Xu and Qiu, Xipeng and Zhu, Xiaodan},
      title = {Improving Image Captioning with Better Use of Caption},
      booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
      year = {2020},
      pages = {7454--7464}, 
      url = {https://www.aclweb.org/anthology/2020.acl-main.664}
    }
    
  7. Heterogeneous Graph Neural Networks for Extractive Document Summarization, ACL, 2020. [BibTeX][PDF][Code]
    Abstract: As a crucial step in extractive document summarization, learning cross-sentence relations has been explored by a plethora of approaches. An intuitive way is to put them in the graph-based neural network, which has a more complex structure for capturing inter-sentence relationships. In this paper, we present a heterogeneous graph-based neural network for extractive summarization (HETERSUMGRAPH), which contains semantic nodes of different granularity levels apart from sentences. These additional nodes act as the intermediary between sentences and enrich the cross-sentence relations. Besides, our graph structure is flexible in natural extension from a single-document setting to multi-document via introducing document nodes. To our knowledge, we are the first one to introduce different types of nodes into graph-based neural networks for extractive document summarization and perform a comprehensive qualitative analysis to investigate their benefits. The code will be released on Github.
    Danqing Wang, Pengfei Liu, Yining Zheng, Xipeng Qiu, Xuanjing Huang.
    [Abstract]
  8. BibTeX:
    @inproceedings{wang-etal-2020-heterogeneous,
      author = {Wang, Danqing and Liu, Pengfei and Zheng, Yining and Qiu, Xipeng and Huang, Xuanjing},
      title = {Heterogeneous Graph Neural Networks for Extractive Document Summarization},
      booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
      year = {2020},
      pages = {6209--6219}, 
      url = {https://www.aclweb.org/anthology/2020.acl-main.553}
    }
    
  9. Extractive Summarization as Text Matching, ACL, 2020. [BibTeX][PDF][Code]
    Abstract: This paper creates a paradigm shift with regard to the way we build neural extractive summarization systems. Instead of following the commonly used framework of extracting sentences individually and modeling the relationship between sentences, we formulate the extractive summarization task as a semantic text matching problem, in which a source document and candidate summaries will be (extracted from the original text) matched in a semantic space. Notably, this paradigm shift to semantic matching framework is well-grounded in our comprehensive analysis of the inherent gap between sentence-level and summary-level extractors based on the property of the dataset. Besides, even instantiating the framework with a simple form of a matching model, we have driven the state-of-the-art extractive result on CNN/DailyMail to a new level (44.41 in ROUGE-1). Experiments on the other five datasets also show the effectiveness of the matching framework. We believe the power of this matching-based summarization framework has not been fully exploited. To encourage more instantiations in the future, we have released our codes, processed dataset, as well as generated summaries in url.
    Ming Zhong, Pengfei Liu, Yiran Chen, Danqing Wang, Xipeng Qiu, Xuanjing Huang.
    [Abstract]
  10. BibTeX:
    @inproceedings{zhong-etal-2020-extractive,
      author = {Zhong, Ming and Liu, Pengfei and Chen, Yiran and Wang, Danqing and Qiu, Xipeng and Huang, Xuanjing},
      title = {Extractive Summarization as Text Matching},
      booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
      year = {2020},
      pages = {6197--6208}, 
      url = {https://www.aclweb.org/anthology/2020.acl-main.552}
    }
    
  11. Multi-Scale Self-Attention for Text Classification, AAAI, 2020. [BibTeX] [PDF]
    Qipeng Guo, Xipeng Qiu, Pengfei Liu, Xiangyang Xue, Zheng Zhang.
  12. BibTeX:
    @inproceedings{guo2020multiscale,
      author = {Qipeng Guo and Xipeng Qiu and Pengfei Liu and Xiangyang Xue and Zheng Zhang},
      title = {Multi-Scale Self-Attention for Text Classification},
      booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
      year = {2020}, 
      url = {https://arxiv.org/abs/1912.00544}
    }
    
  13. Learning Sparse Sharing Architectures for Multiple Tasks, AAAI, 2020. [BibTeX] [PDF] [Code]
    Tianxiang Sun, Yunfan Shao, Xiaonan Li, Pengfei Liu, Hang Yan, Xipeng Qiu, Xuanjing Huang.
  14. BibTeX:
    @inproceedings{sun2020sparsing,
      author = {Tianxiang Sun and Yunfan Shao and Xiaonan Li and Pengfei Liu and Hang Yan and Xipeng Qiu and Xuanjing Huang},
      title = {Learning Sparse Sharing Architectures for Multiple Tasks},
      booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
      year = {2020}
    }
    

    [2019]

  15. How to Fine-Tune BERT for Text Classification?, CCL (Best Paper Award), 2019. [BibTeX][PDF]
    Chi Sun, Xipeng Qiu, Yige Xu, Xuanjing Huang.
  16. BibTeX:
    @inproceedings{sun2019finetune,
      author = {Chi Sun and Xipeng Qiu and Yige Xu and Xuanjing Huang},
      title = {How to Fine-Tune BERT for Text Classification?},
      booktitle = {Proceedings of China National Conference on Computational Linguistics},
      year = {2019},
      pages = {194--206}, 
      url = {https://arxiv.org/abs/1905.05583}
    }
    
  17. Star-Transformer, NAACL, 2019. [BibTeX][PDF]
    Abstract: Although Transformer has achieved great successes on many NLP tasks, its heavy structure with fully-connected attention connections leads to dependencies on large training data. In this paper, we present Star-Transformer, a lightweight alternative by careful sparsification. To reduce model complexity, we replace the fully-connected structure with a star-shaped topology, in which every two non-adjacent nodes are connected through a shared relay node. Thus, complexity is reduced from quadratic to linear, while preserving the capacity to capture both local composition and long-range dependency. The experiments on four tasks (22 datasets) show that Star-Transformer achieved significant improvements against the standard Transformer for the modestly sized datasets.
    Qipeng Guo, Xipeng Qiu, Pengfei Liu, Yunfan Shao, Xiangyang Xue, Zheng Zhang.
    [Abstract]
  18. BibTeX:
    @inproceedings{guo2019star,
      author = {Guo, Qipeng and Qiu, Xipeng and Liu, Pengfei and Shao, Yunfan and Xue, Xiangyang and Zhang, Zheng},
      title = {Star-Transformer},
      booktitle = {Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
      year = {2019},
      pages = {1315--1325}, 
      url = {https://www.aclweb.org/anthology/N19-1133}
    }
    
  19. VCWE: Visual Character-Enhanced Word Embeddings, NAACL, 2019. [BibTeX][PDF]
    Abstract: Chinese is a logographic writing system, and the shape of Chinese characters contain rich syntactic and semantic information. In this paper, we propose a model to learn Chinese word embeddings via three-level composition: (1) a convolutional neural network to extract the intra-character compositionality from the visual shape of a character; (2) a recurrent neural network with self-attention to compose character representation into word embeddings; (3) the Skip-Gram framework to capture non-compositionality directly from the contextual information. Evaluations demonstrate the superior performance of our model on four tasks: word similarity, sentiment analysis, named entity recognition and part-of-speech tagging.
    Chi Sun, Xipeng Qiu, Xuanjing Huang.
    [Abstract]
  20. BibTeX:
    @inproceedings{sun2019vcwe,
      author = {Sun, Chi and Qiu, Xipeng and Huang, Xuanjing},
      title = {VCWE: Visual Character-Enhanced Word Embeddings},
      booktitle = {Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)},
      year = {2019},
      pages = {2710--2719}, 
      url = {https://www.aclweb.org/anthology/N19-1277}
    }
    
  21. Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation, ACL, 2019. [BibTeX][PDF][Code]
    Ning Dai, Jianze Liang, Xipeng Qiu, Xuanjing Huang.
  22. BibTeX:
    @inproceedings{dai2019style,
      author = {Ning Dai and Jianze Liang and Xipeng Qiu and Xuanjing Huang},
      title = {Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation},
      booktitle = {Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},
      year = {2019},
      pages = {5997--6007}, 
      url = {https://www.aclweb.org/anthology/P19-1601/}
    }
    
  23. Searching for Effective Neural Extractive Summarization: What Works and What's Next, ACL, 2019. [BibTeX][PDF][Code]
    Ming Zhong, Pengfei Liu, Xipeng Qiu, Xuanjing Huang.
  24. BibTeX:
    @inproceedings{zhong2019sum,
      author = {Ming Zhong and Pengfei Liu and Xipeng Qiu and Xuanjing Huang},
      title = {Searching for Effective Neural Extractive Summarization: What Works and What's Next},
      booktitle = {Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},
      year = {2019},
      pages = {1049--1058}, 
      url = {https://www.aclweb.org/anthology/P19-1100/}
    }
    
  25. Switch-LSTMs for Multi-Criteria Chinese Word Segmentation, AAAI, 2019. [BibTeX][PDF]
    Jingjing Gong, Xinchi Chen, Tao Gui, Xipeng Qiu.
  26. BibTeX:
    @inproceedings{gong2019switch,
      author = {Jingjing Gong and Xinchi Chen and Tao Gui and Xipeng Qiu},
      title = {Switch-LSTMs for Multi-Criteria Chinese Word Segmentation},
      booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
      year = {2019},
      pages = {6457--6464}, 
      url = {https://arxiv.org/abs/1812.08033}
    }
    
  27. Learning Multi-Task Communication with Message Passing for Sequence Learning, AAAI, 2019. [BibTeX][PDF]
    Pengfei Liu, Jie Fu, Yue Dong, Xipeng Qiu, Jackie Chi Kit Cheung.
  28. BibTeX:
    @inproceedings{liu2019multi,
      author = {Pengfei Liu and Jie Fu and Yue Dong and Xipeng Qiu and Jackie Chi Kit Cheung},
      title = {Learning Multi-Task Communication with Message Passing for Sequence Learning},
      booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
      year = {2019},
      pages = {4360--4367}, 
      url = {https://aaai.org/ojs/index.php/AAAI/article/view/4346}
    }
    
  29. Text Information Aggregation with Centrality Attention, SCIENCE CHINA Information Sciences (SCIS) , 2019. [BibTeX]
    JingJing Gong, Hang Yan, Yining Zheng, Qipeng Guo, Xipeng Qiu, Xuanjing Huang.
  30. BibTeX:
    @article{gong2019centrality,
      author = {JingJing Gong and Hang Yan and Yining Zheng and Qipeng Guo and Xipeng Qiu and Xuanjing Huang},
      title = {Text Information Aggregation with Centrality Attention},
      journal = {SCIENCE CHINA Information Sciences},
      year = {2019}
    }
    
  31. Low-rank and Locality Constrained Self-Attention for Sequence Modeling, IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP) , 2019. [BibTeX]
    Qipeng Guo, Xipeng Qiu, Xiangyang Xue, Zheng Zhang.
  32. BibTeX:
    @article{guo2019low,
      author = {Guo, Qipeng and Qiu, Xipeng and Xue, Xiangyang and Zhang, Zheng},
      title = {Low-rank and Locality Constrained Self-Attention for Sequence Modeling},
      journal = {IEEE/ACM Transactions on Audio, Speech, and Language Processing},
      year = {2019}
    }
    
  33. Co-attention Memory Network for Multimodal Microblog's Hashtag Recommendation, IEEE Transactions on Knowledge and Data Engineering (TKDE) , 2019. [BibTeX]
    Renfeng Ma, Xipeng Qiu, Qi Zhang, Xiangkun Hu, Yu-Gang Jiang, Xuanjing Huang.
  34. BibTeX:
    @article{ma2019co,
      author = {Ma, Renfeng and Qiu, Xipeng and Zhang, Qi and Hu, Xiangkun and Jiang, Yu-Gang and Huang, Xuanjing},
      title = {Co-attention Memory Network for Multimodal Microblog's Hashtag Recommendation},
      journal = {IEEE Transactions on Knowledge and Data Engineering},
      year = {2019}
    }
    
  35. Chinese Word Segmentation via BiLSTM+Semi-CRF with Relay Node, Journal of Computer Science and Technology (JCST) , 2019. [BibTeX]
    Nuo Qun, Hang Yan, Xipeng Qiu, Xuanjing Huang.
  36. BibTeX:
    @article{qun2019chinese,
      author = {Nuo Qun and Hang Yan and Xipeng Qiu and Xuanjing Huang},
      title = {Chinese Word Segmentation via BiLSTM+Semi-CRF with Relay Node},
      journal = {Journal of Computer Science and Technology},
      year = {2019}
    }
    
  37. Sequence Labeling with Deep Gated Dual Path CNN, IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP) , 2019. [BibTeX]
    Lujun Zhao, Xipeng Qiu, Qi Zhang, Xuanjing Huang.
  38. BibTeX:
    @article{zhao2019sequence,
      author = {Zhao, Lujun and Qiu, Xipeng and Zhang, Qi and Huang, Xuanjing},
      title = {Sequence Labeling with Deep Gated Dual Path CNN},
      journal = {IEEE/ACM Transactions on Audio, Speech, and Language Processing},
      year = {2019}
    }
    

    [2018]

  39. Information Aggregation via Dynamic Routing for Sequence Encoding, COLING, 2018. [BibTeX][PDF]
    Jingjing Gong, Xipeng Qiu, Shaojing Wang, Xuanjing Huang.
  40. BibTeX:
    @inproceedings{gong2018information,
      author = {Jingjing Gong and Xipeng Qiu and Shaojing Wang and Xuanjing Huang},
      title = {Information Aggregation via Dynamic Routing for Sequence Encoding},
      booktitle = {Proceedings of the 27th International Conference on Computational Linguistics},
      year = {2018},
      url = {https://arxiv.org/abs/1806.01501}
    }
    
  41. Convolutional Interaction Network for Natural Language Inference, EMNLP, 2018. [BibTeX][PDF]
    Jingjing Gong, Xipeng Qiu, Xinchi Chen, Dong Liang, Xuanjing Huang.
  42. BibTeX:
    @inproceedings{gong2018convolutional,
      author = {Gong, Jingjing and Qiu, Xipeng and Chen, Xinchi and Liang, Dong and Huang, Xuanjing},
      title = {Convolutional Interaction Network for Natural Language Inference},
      booktitle = {Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing},
      year = {2018},
      pages = {1576--1585},
      url = {http://aclweb.org/anthology/D18-1186}
    }
    
  43. Same Representation, Different Attentions: Shareable Sentence Representation Learning from Multiple Tasks, IJCAI, 2018. [BibTeX][PDF]
    Renjie Zheng, Junkun Chen, Xipeng Qiu.
  44. BibTeX:
    @inproceedings{zheng2018same,
      author = {Zheng, Renjie and Chen, Junkun and Qiu, Xipeng},
      title = {Same Representation, Different Attentions: Shareable Sentence Representation Learning from Multiple Tasks},
      booktitle = {Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence},
      year = {2018},
      url = {https://arxiv.org/abs/1804.08139}
    }
    
  45. Toward Diverse Text Generation with Inverse Reinforcement Learning, IJCAI, 2018. [BibTeX][PDF]
    Zhan Shi, Xinchi Chen, Xipeng Qiu, Xuanjing Huang.
  46. BibTeX:
    @inproceedings{shi2018towards,
      author = {Shi, Zhan and Chen, Xinchi and Qiu, Xipeng and Huang, Xuanjing},
      title = {Towards Diverse Text Generation with Inverse Reinforcement Learning},
      booktitle = {Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence},
      year = {2018},
      url = {https://arxiv.org/abs/1804.11258}
    }
    
  47. Incorporating Discriminator in Sentence Generation: a Gibbs Sampling Method, AAAI, 2018. [BibTeX][PDF]
    Jinyue Su, Jiacheng Xu, Xipeng Qiu, Xuanjing Huang.
  48. BibTeX:
    @inproceedings{su2018incorporating,
      author = {Su, Jinyue and Xu, Jiacheng and Qiu, Xipeng and Huang, Xuanjing},
      title = {Incorporating Discriminator in Sentence Generation: a Gibbs Sampling Method},
      booktitle = {Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence},
      year = {2018},
      url = {https://arxiv.org/abs/1802.08970}
    }
    
  49. Meta Multi-Task Learning for Sequence Modeling, AAAI, 2018. [BibTeX][PDF]
    Junkun Chen, Xipeng Qiu, Pengfei Liu, Xuanjing Huang.
  50. BibTeX:
    @inproceedings{chen2018meta,
      author = {Chen, Junkun and Qiu, Xipeng and Liu, Pengfei and Huang, Xuanjing},
      title = {Meta Multi-Task Learning for Sequence Modeling},
      booktitle = {Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence},
      year = {2018},
      url = {https://arxiv.org/abs/1802.08969}
    }
    

    [2017]

  51. Adaptive Semantic Compositionality for Sentence Modelling, IJCAI, 2017. [BibTeX][PDF]
    Pengfei Liu, Xipeng Qiu, Xuanjing Huang.
  52. BibTeX:
    @inproceedings{liu2017adaptive,
      author = {Pengfei Liu and Xipeng Qiu and Xuanjing Huang},
      title = {Adaptive Semantic Compositionality for Sentence Modelling},
      booktitle = {Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-17},
      year = {2017},
      pages = {4061--4067},
      url = {https://www.ijcai.org/proceedings/2017/0567.pdf}
    }
    
  53. A Feature-Enriched Neural Model for Joint Chinese Word Segmentation and Part-of-Speech Tagging, IJCAI, 2017. [BibTeX][PDF]
    Xinchi Chen, Xipeng Qiu, Xuanjing Huang.
  54. BibTeX:
    @inproceedings{chen2017feature,
      author = {Xinchi Chen and Xipeng Qiu and Xuanjing Huang},
      title = {A Feature-Enriched Neural Model for Joint Chinese Word Segmentation and Part-of-Speech Tagging},
      booktitle = {Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-17},
      year = {2017},
      pages = {3960--3966},
      url = {https://www.ijcai.org/proceedings/2017/0553.pdf}
    }
    
  55. Knowledge Graph Representation with Jointly Structural and Textual Encoding, IJCAI, 2017. [BibTeX][PDF]
    Jiacheng Xu, Xipeng Qiu, Kan Chen, Xuanjing Huang.
  56. BibTeX:
    @inproceedings{xu2017knowledge,
      author = {Jiacheng Xu and Xipeng Qiu and Kan Chen and Xuanjing Huang},
      title = {Knowledge Graph Representation with Jointly Structural and Textual Encoding},
      booktitle = {Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence},
      year = {2017},
      pages = {1318--1324},
      url = {https://www.ijcai.org/proceedings/2017/0183.pdf}
    }
    
  57. Dynamic Compositional Neural Networks over Tree Structure, IJCAI, 2017. [BibTeX] [DOI][PDF]
    Pengfei Liu, Xipeng Qiu, Xuanjing Huang.
  58. BibTeX:
    @inproceedings{liu2017dynamic,
      author = {Pengfei Liu and Xipeng Qiu and Xuanjing Huang},
      title = {Dynamic Compositional Neural Networks over Tree Structure},
      booktitle = {Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence},
      year = {2017},
      pages = {4054--4060},
      url = {https://www.ijcai.org/proceedings/2017/0566.pdf},
      doi = {https://doi.org/10.24963/ijcai.2017/566}
    }
    
  59. Adversarial Multi-task Learning for Text Classification, ACL, 2017. [BibTeX][PDF]
    Pengfei Liu, Xipeng Qiu, Xuanjing Huang.
  60. BibTeX:
    @inproceedings{liu2017adversarial,
      author = {Pengfei Liu and Xipeng Qiu and Xuanjing Huang},
      title = {Adversarial Multi-task Learning for Text Classification},
      booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics},
      year = {2017},
      pages = {1--10},
      url = {http://aclweb.org/anthology/P/P17/P17-1001.pdf}
    }
    
  61. Adversarial Multi-Criteria Learning for Chinese Word Segmentation, ACL (Outstanding Paper Award), 2017. [BibTeX][PDF]
    Xinchi Chen, Zhan Shi, Xipeng Qiu, Xuanjing Huang.
  62. BibTeX:
    @inproceedings{chen2017adversarial,
      author = {Xinchi Chen and Zhan Shi and Xipeng Qiu and Xuanjing Huang},
      title = {Adversarial Multi-Criteria Learning for Chinese Word Segmentation},
      booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics},
      year = {2017},
      pages = {1193--1203},
      url = {http://aclweb.org/anthology/P/P17/P17-1110.pdf}
    }
    
  63. Idiom-Aware Compositional Distributed Semantics, EMNLP, 2017. [BibTeX][PDF]
    Pengfei Liu, Kaiyu Qian, Xipeng Qiu, Xuanjing Huang.
  64. BibTeX:
    @inproceedings{liu2017idiom,
      author = {Liu, Pengfei and Qian, Kaiyu and Qiu, Xipeng and Huang, Xuanjing},
      title = {Idiom-Aware Compositional Distributed Semantics},
      booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
      year = {2017},
      pages = {1215--1224},
      url = {http://www.aclweb.org/anthology/D17-1125}
    }
    

    [2016]

  65. Cached Long Short-Term Memory Neural Networks for Document-Level Sentiment Classification, EMNLP, 2016. [BibTeX][PDF]
    Jiacheng Xu, Danlu Chen, Xipeng Qiu, Xuanjing Huang.
  66. BibTeX:
    @inproceedings{xu2016cached,
      author = {Jiacheng Xu and Danlu Chen and Xipeng Qiu and Xuanjing Huang},
      title = {Cached Long Short-Term Memory Neural Networks for Document-Level Sentiment Classification},
      booktitle = {Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing},
      year = {2016},
      url = {https://aclweb.org/anthology/D16-1172}
    }
    
  67. Analyzing Linguistic Knowledge in Sequential Model of Sentence, EMNLP, 2016. [BibTeX][PDF]
    Peng Qian, Xipeng Qiu, Xuanjing Huang.
  68. BibTeX:
    @inproceedings{qian2016analyzing,
      author = {Peng Qian and Xipeng Qiu and Xuanjing Huang},
      title = {Analyzing Linguistic Knowledge in Sequential Model of Sentence},
      booktitle = {Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing},
      year = {2016},
      url = {https://aclweb.org/anthology/D16-1079}
    }
    
  69. Modelling Interaction of Sentence Pair with Coupled-LSTMs, EMNLP, 2016. [BibTeX][PDF]
    Pengfei Liu, Xipeng Qiu, Yaqian Zhou, Jifan Chen, Xuanjing Huang.
  70. BibTeX:
    @inproceedings{liu2016modelling,
      author = {Liu, Pengfei and Qiu, Xipeng and Zhou, Yaqian and Chen, Jifan and Huang, Xuanjing},
      title = {Modelling Interaction of Sentence Pair with Coupled-LSTMs},
      booktitle = {Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing},
      year = {2016},
      url = {https://aclweb.org/anthology/D16-1176}
    }
    
  71. Deep Multi-Task Learning with Shared Memory, EMNLP, 2016. [BibTeX][PDF]
    Pengfei Liu, Xipeng Qiu, Xuanjing Huang.
  72. BibTeX:
    @inproceedings{liu2016deep-multitask,
      author = {Liu, Pengfei and Qiu, Xipeng and Huang, Xuanjing},
      title = {Deep Multi-Task Learning with Shared Memory},
      booktitle = {Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing},
      year = {2016},
      url = {https://aclweb.org/anthology/D16-1012}
    }
    
  73. Bridging LSTM Architecture and the Neural Dynamics during Reading, IJCAI, 2016. [BibTeX][PDF]
    Peng Qian, Xipeng Qiu, Xuanjing Huang.
  74. BibTeX:
    @inproceedings{qian2016bridge,
      author = {Peng Qian and Xipeng Qiu and Xuanjing Huang},
      title = {Bridging LSTM Architecture and the Neural Dynamics during Reading},
      booktitle = {Proceedings of International Joint Conference on Artificial Intelligence},
      year = {2016},
      url = {https://arxiv.org/abs/1604.06635}
    }
    
  75. Recurrent Neural Network for Text Classification with Multi-Task Learning, IJCAI, 2016. [BibTeX][PDF]
    Pengfei Liu, Xipeng Qiu, Xuanjing Huang.
  76. BibTeX:
    @inproceedings{liu2016recurrent,
      author = {Pengfei Liu and Xipeng Qiu and Xuanjing Huang},
      title = {Recurrent Neural Network for Text Classification with Multi-Task Learning},
      booktitle = {Proceedings of International Joint Conference on Artificial Intelligence},
      year = {2016},
      url = {https://arxiv.org/abs/1605.05101}
    }
    
  77. Investigating Language Universal and Specific in Word Embedding, ACL, 2016. [BibTeX][PDF]
    Peng Qian, Xipeng Qiu, Xuanjing Huang.
  78. BibTeX:
    @inproceedings{qian2016investigating,
      author = {Peng Qian and Xipeng Qiu and Xuanjing Huang},
      title = {Investigating Language Universal and Specific in Word Embedding},
      booktitle = {Proceedings of Annual Meeting of the Association for Computational Linguistics},
      year = {2016},
      url = {http://aclweb.org/anthology/P/P16/P16-1140.pdf}
    }
    
  79. A New Psychometric-inspired Evaluation Metric for Chinese Word Segmentation, ACL, 2016. [BibTeX][PDF]
    Peng Qian, Xipeng Qiu, Xuanjing Huang.
  80. BibTeX:
    @inproceedings{qian2016new,
      author = {Peng Qian and Xipeng Qiu and Xuanjing Huang},
      title = {A New Psychometric-inspired Evaluation Metric for Chinese Word Segmentation},
      booktitle = {Proceedings of Annual Meeting of the Association for Computational Linguistics},
      year = {2016},
      url = {http://aclweb.org/anthology/P/P16/P16-1206.pdf}
    }
    
  81. Deep Fusion LSTMs for Text Semantic Matching, ACL, 2016. [BibTeX][PDF]
    Pengfei Liu, Xipeng Qiu, Jifan Chen, Xuanjing Huang.
  82. BibTeX:
    @inproceedings{liu2016deep,
      author = {Pengfei Liu and Xipeng Qiu and Jifan Chen and Xuanjing Huang},
      title = {Deep Fusion LSTMs for Text Semantic Matching},
      booktitle = {Proceedings of Annual Meeting of the Association for Computational Linguistics},
      year = {2016},
      url = {http://aclweb.org/anthology/P/P16/P16-1098.pdf}
    }
    
  83. Implicit Discourse Relation Detection via a Deep Architecture with Gated Relevance Network, ACL, 2016. [BibTeX][PDF]
    Jifan Chen, Qi Zhang, Pengfei Liu, Xipeng Qiu, Xuanjing Huang.
  84. BibTeX:
    @inproceedings{chen2016implicit,
      author = {Jifan Chen and Qi Zhang and Pengfei Liu and Xipeng Qiu and Xuanjing Huang},
      title = {Implicit Discourse Relation Detection via a Deep Architecture with Gated Relevance Network},
      booktitle = {Proceedings of Annual Meeting of the Association for Computational Linguistics},
      year = {2016},
      url = {http://aclweb.org/anthology/P/P16/P16-1163.pdf}
    }
    

    [2015]

  85. Multi-Timescale Long Short-Term Memory Neural Network for Modelling Sentences and Documents, EMNLP, 2015. [BibTeX][PDF]
    PengFei Liu, Xipeng Qiu, Xinchi Chen, Shiyu Wu, Xuanjing Huang.
  86. BibTeX:
    @inproceedings{liu2015multitimescale,
      author = {PengFei Liu and Xipeng Qiu and Xinchi Chen and Shiyu Wu and Xuanjing Huang},
      title = {Multi-Timescale Long Short-Term Memory Neural Network for Modelling Sentences and Documents},
      booktitle = {Proceedings of the Conference on Empirical Methods in Natural Language Processing},
      year = {2015},
      url = {http://www.aclweb.org/anthology/D/D15/D15-1280.pdf}
    }
    
  87. Transition-based Dependency Parsing Using Two Heterogeneous Gated Recursive Neural Networks, EMNLP, 2015. [BibTeX][PDF]
    Xinchi Chen, Yaqian Zhou, Chenxi Zhu, Xipeng Qiu, Xuanjing Huang.
  88. BibTeX:
    @inproceedings{chen2015transition,
      author = {Xinchi Chen and Yaqian Zhou and Chenxi Zhu and Xipeng Qiu and Xuanjing Huang},
      title = {Transition-based Dependency Parsing Using Two Heterogeneous Gated Recursive Neural Networks},
      booktitle = {Proceedings of the Conference on Empirical Methods in Natural Language Processing},
      year = {2015},
      url = {http://www.aclweb.org/anthology/D/D15/D15-1215.pdf}
    }
    
  89. Sentence Modeling with Gated Recursive Neural Network, EMNLP, 2015. [BibTeX][PDF]
    Xinchi Chen, Xipeng Qiu, Chenxi Zhu, Shiyu Wu, Xuanjing Huang.
  90. BibTeX:
    @inproceedings{chen2015sentence,
      author = {Xinchi Chen and Xipeng Qiu and Chenxi Zhu and Shiyu Wu and Xuanjing Huang},
      title = {Sentence Modeling with Gated Recursive Neural Network},
      booktitle = {Proceedings of the Conference on Empirical Methods in Natural Language Processing},
      year = {2015},
      url = {http://www.aclweb.org/anthology/D/D15/D15-1092.pdf}
    }
    
  91. Long Short-Term Memory Neural Networks for Chinese Word Segmentation, EMNLP, 2015. [BibTeX][PDF]
    Xinchi Chen, Xipeng Qiu, Chenxi Zhu, Pengfei Liu, Xuanjing Huang.
  92. BibTeX:
    @inproceedings{chen2015long,
      author = {Xinchi Chen and Xipeng Qiu and Chenxi Zhu and Pengfei Liu and Xuanjing Huang},
      title = {Long Short-Term Memory Neural Networks for Chinese Word Segmentation},
      booktitle = {Proceedings of the Conference on Empirical Methods in Natural Language Processing},
      year = {2015},
      url = {http://www.aclweb.org/anthology/D/D15/D15-1141.pdf}
    }
    
  93. Convolutional Neural Tensor Network Architecture for Community-based Question Answering, IJCAI, 2015. [BibTeX][PDF]
    Xipeng Qiu, Xuanjing Huang.
  94. BibTeX:
    @inproceedings{qiu2015convolutional,
      author = {Xipeng Qiu and Xuanjing Huang},
      title = {Convolutional Neural Tensor Network Architecture for Community-based Question Answering},
      booktitle = {Proceedings of International Joint Conference on Artificial Intelligence},
      year = {2015},
      url = {http://ijcai.org/papers15/Papers/IJCAI15-188.pdf}
    }
    
  95. Learning Context-Sensitive Word Embeddings with Neural Tensor Skip-Gram Model, IJCAI, 2015. [BibTeX][PDF]
    PengFei Liu, Xipeng Qiu, Xuanjing Huang.
  96. BibTeX:
    @inproceedings{liu2015learning,
      author = {PengFei Liu and Xipeng Qiu and Xuanjing Huang},
      title = {Learning Context-Sensitive Word Embeddings with Neural Tensor Skip-Gram Model},
      booktitle = {Proceedings of International Joint Conference on Artificial Intelligence},
      year = {2015},
      url = {http://ijcai.org/papers15/Papers/IJCAI15-185.pdf}
    }
    
  97. A Re-Ranking Model For Dependency Parser With Recursive Convolutional Neural Network, ACL, 2015. [BibTeX][PDF]
    Chenxi Zhu, Xipeng Qiu, Xinchi Chen, Xuanjing Huang.
  98. BibTeX:
    @inproceedings{zhu2015reranking,
      author = {Chenxi Zhu and Xipeng Qiu and Xinchi Chen and Xuanjing Huang},
      title = {A Re-Ranking Model For Dependency Parser With Recursive Convolutional Neural Network},
      booktitle = {Proceedings of Annual Meeting of the Association for Computational Linguistics},
      year = {2015},
      url = {http://www.aclweb.org/anthology/P/P15/P15-1112.pdf}
    }
    
  99. Gated Recursive Neural Network For Chinese Word Segmentation, ACL, 2015. [BibTeX][PDF]
    Xinchi Chen, Xipeng Qiu, Chenxi Zhu, Xuanjing Huang.
  100. BibTeX:
    @inproceedings{chen2015gated,
      author = {Xinchi Chen and Xipeng Qiu and Chenxi Zhu and Xuanjing Huang},
      title = {Gated Recursive Neural Network For Chinese Word Segmentation},
      booktitle = {Proceedings of Annual Meeting of the Association for Computational Linguistics},
      year = {2015},
      url = {http://www.aclweb.org/anthology/P/P15/P15-1168.pdf}
    }
    

    [2014 and before]

  101. Automatic Corpus Expansion for Chinese Word Segmentation by Exploiting the Redundancy of Web Information, COLING, 2014. [BibTeX][PDF]
    Xipeng Qiu, ChaoChao Huang, Xuanjing Huang.
  102. BibTeX:
    @inproceedings{qiu2014automatic,
      author = {Qiu, Xipeng and Huang, ChaoChao and Huang, Xuanjing},
      title = {Automatic Corpus Expansion for Chinese Word Segmentation by Exploiting the Redundancy of Web Information},
      booktitle = {Proceedings of the 25th International Conference on Computational Linguistics},
      year = {2014},
      pages = {1154--1164},
      url = {http://anthology.aclweb.org/C/C14/C14-1109.pdf}
    }
    
  103. Learning Topical Translation Model for Microblog Hashtag Suggestion, IJCAI, 2013. [BibTeX]
    Zhuoye Ding, Xipeng Qiu, Qi Zhang, Xuanjing Huang.
  104. BibTeX:
    @inproceedings{ding2013learning,
      author = {Ding, Zhuoye and Qiu, Xipeng and Zhang, Qi and Huang, Xuanjing},
      title = {Learning Topical Translation Model for Microblog Hashtag Suggestion},
      booktitle = {Proceedings of the Twenty-Third international joint conference on Artificial Intelligence},
      year = {2013}
    }
    
  105. Joint Chinese Word Segmentation and POS Tagging on Heterogeneous Annotated Corpora with Multiple Task Learning, EMNLP, 2013. [BibTeX][PDF]
    Xipeng Qiu, Jiayi Zhao, Xuanjing Huang.
  106. BibTeX:
    @inproceedings{qiu2013joint,
      author = {Qiu, Xipeng and Zhao, Jiayi and Huang, Xuanjing},
      title = {Joint Chinese Word Segmentation and POS Tagging on Heterogeneous Annotated Corpora with Multiple Task Learning},
      booktitle = {Proceedings of the Conference on Empirical Methods in Natural Language Processing},
      year = {2013},
      pages = {658--668},
      url = {http://www.aclweb.org/anthology/D/D13/D13-1062.pdf}
    }
    
  107. FudanNLP: A Toolkit for Chinese Natural Language Processing, ACL, 2013. [BibTeX]
    Xipeng Qiu, Qi Zhang, Xuanjing Huang.
  108. BibTeX:
    @inproceedings{Qiu:2013,
      author = {Xipeng Qiu and Qi Zhang and Xuanjing Huang},
      title = {FudanNLP: A Toolkit for Chinese Natural Language Processing},
      booktitle = {Proceedings of Annual Meeting of the Association for Computational Linguistics},
      year = {2013}
    }
    
  109. Recognizing Inference in Texts with Markov Logic Networks, ACM Transactions on Asian Language Information Processing (TALIP) , Vol. 11(4), pp. 15:1-15:23, 2012. [BibTeX]
    Xipeng Qiu, Ling Cao, Zhao Liu, Xuanjing Huang.
  110. BibTeX:
    @article{Qiu:2012:RIT:2382593.2382597,
      author = {Qiu, Xipeng and Cao, Ling and Liu, Zhao and Huang, Xuanjing},
      title = {Recognizing Inference in Texts with Markov Logic Networks},
      journal = {ACM Transactions on Asian Language Information Processing},
      year = {2012},
      volume = {11},
      number = {4},
      pages = {15:1--15:23}
    }
    
  111. Part-of-Speech Tagging for Chinese-English Mixed Texts with Dynamic Features, EMNLP-CONLL, 2012. [BibTeX][PDF]
    Jiayi Zhao, Xipeng Qiu, Shu Zhang, Feng Ji, Xuanjing Huang.
  112. BibTeX:
    @inproceedings{zhao2012partofspeech,
      author = {Zhao, Jiayi and Qiu, Xipeng and Zhang, Shu and Ji, Feng and Huang, Xuanjing},
      title = {Part-of-Speech Tagging for Chinese-English Mixed Texts with Dynamic Features},
      booktitle = {Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning},
      year = {2012},
      url = {http://www.aclweb.org/anthology/D/D12/D12-1126}
    }
    
  113. Joint Segmentation and Tagging with Coupled Sequences Labeling, COLING, 2012. [BibTeX][PDF]
    Xipeng Qiu, Feng Ji, Jiayi Zhao, Xuanjing Huang.
  114. BibTeX:
    @inproceedings{Qiu:2012,
      author = {Qiu, Xipeng and Ji, Feng and Zhao, Jiayi and Huang, Xuanjing},
      title = {Joint Segmentation and Tagging with Coupled Sequences Labeling},
      booktitle = {Proceedings of International Conference on Computational Linguistics},
      year = {2012},
      pages = {951--964},
      url = {http://www.aclweb.org/anthology/C12-2093}
    }
    
  115. Hierarchical Text Classification with Latent Concepts, ACL-HLT, 2011. [BibTeX]
    Xipeng Qiu, Xuanjing Huang, Zhao Liu, Jinlong Zhou.
  116. BibTeX:
    @inproceedings{qiu2011hierarchical,
      author = {Xipeng Qiu and Xuanjing Huang and Zhao Liu and Jinlong Zhou},
      title = {Hierarchical Text Classification with Latent Concepts},
      booktitle = {Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies},
      year = {2011}
    }
    
  117. An Effective Feature Selection Method for Text Categorization, PAKDD, 2011. [BibTeX]
    Xipeng Qiu, Jinlong Zhou, Xuanjing Huang.
  118. BibTeX:
    @inproceedings{Qiu:2011a,
      author = {Xipeng Qiu and Jinlong Zhou and Xuanjing Huang},
      title = {An Effective Feature Selection Method for Text Categorization},
      booktitle = {Proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining},
      year = {2011}
    }
    
  119. Detecting Hedge Cues and their Scopes with Average Perceptron, CONLL, 2010. [BibTeX][PDF]
    Feng Ji, Xipeng Qiu, Xuanjing Huang.
  120. BibTeX:
    @inproceedings{ji2010detecting,
      author = {Feng Ji and Xipeng Qiu and Xuanjing Huang},
      title = {Detecting Hedge Cues and their Scopes with Average Perceptron},
      booktitle = {Fourteenth Conference on Computational Natural Language Learning},
      year = {2010}, 
      url = {https://www.aclweb.org/anthology/W10-3005/}
    }
    
  121. Info-Margin Maximization for Feature Extraction, Pattern Recognition Letters (PRL) , Vol. 30, pp. 1516-1522, 2009. [BibTeX]
    Xipeng Qiu, Lide Wu.
  122. BibTeX:
    @article{qiu2009infomargin,
      author = {Xipeng Qiu and Lide Wu},
      title = {Info-Margin Maximization for Feature Extraction},
      journal = {Pattern Recognition Letters},
      year = {2009},
      volume = {30},
      pages = {1516--1522}
    }
    
  123. Hierarchical Multi-Class Text Categorization with Global Margin Maximization, ACL-IJCNLP, 2009. [BibTeX]
    Xipeng Qiu, Wenjun Gao, Xuanjing Huang.
  124. BibTeX:
    @inproceedings{Qiu:2009,
      author = {Qiu, Xipeng and Gao, Wenjun and Huang, Xuanjing},
      title = {Hierarchical Multi-Class Text Categorization with Global Margin Maximization},
      booktitle = {Proceedings of the Joint Conference of the Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP},
      year = {2009},
      pages = {165--168}
    }
    
  125. Two-dimensional nearest neighbor discriminant analysis, Neurocomputing (NeuCom) , Vol. 70(13-15), pp. 2572-2575, 2007. [BibTeX]
    Xipeng Qiu, Lide Wu.
  126. BibTeX:
    @article{qiu2007two,
      author = {Xipeng Qiu and Lide Wu},
      title = {Two-dimensional nearest neighbor discriminant analysis},
      journal = {Neurocomputing},
      year = {2007},
      volume = {70},
      number = {13-15},
      pages = {2572-2575},
    }
    
  127. Stepwise Nearest Neighbor Discriminant Analysis, IJCAI, 2005. [BibTeX][PDF]
    Xipeng Qiu, Lide Wu.
  128. BibTeX:
    @inproceedings{qiu2005stepwise,
      author = {Xipeng Qiu and Lide Wu},
      title = {Stepwise Nearest Neighbor Discriminant Analysis},
      booktitle = {Proceedings of the international joint conference on Artificial Intelligence},
      year = {2005},
      pages = {829-834},
    }
    
  129. Face Recognition by Stepwise Nonparametric Margin Maximum Criterion, ICCV, 2005. [BibTeX][PDF]
    Xipeng Qiu, Lide Wu.
  130. BibTeX:
    @inproceedings{Qiu:2005c,
      author = {Xipeng Qiu and Lide Wu},
      title = {Face Recognition by Stepwise Nonparametric Margin Maximum Criterion},
      booktitle = {Proc. of IEEE Conf. on Comput. Vision},
      year = {2005},
      pages = {1567-1572},
    }