Xian Qian


2017

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A non-DNN Feature Engineering Approach to Dependency Parsing – FBAML at CoNLL 2017 Shared Task
Xian Qian | Yang Liu
Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies

For this year’s multilingual dependency parsing shared task, we developed a pipeline system, which uses a variety of features for each of its components. Unlike the recent popular deep learning approaches that learn low dimensional dense features using non-linear classifier, our system uses structured linear classifiers to learn millions of sparse features. Specifically, we trained a linear classifier for sentence boundary prediction, linear chain conditional random fields (CRFs) for tokenization, part-of-speech tagging and morph analysis. A second order graph based parser learns the tree structure (without relations), and fa linear tree CRF then assigns relations to the dependencies in the tree. Our system achieves reasonable performance – 67.87% official averaged macro F1 score

2015

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Feature Selection in Kernel Space: A Case Study on Dependency Parsing
Xian Qian | Yang Liu
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)

2014

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Polynomial Time Joint Structural Inference for Sentence Compression
Xian Qian | Yang Liu
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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2-Slave Dual Decomposition for Generalized Higher Order CRFs
Xian Qian | Yang Liu
Transactions of the Association for Computational Linguistics, Volume 2

We show that the decoding problem in generalized Higher Order Conditional Random Fields (CRFs) can be decomposed into two parts: one is a tree labeling problem that can be solved in linear time using dynamic programming; the other is a supermodular quadratic pseudo-Boolean maximization problem, which can be solved in cubic time using a minimum cut algorithm. We use dual decomposition to force their agreement. Experimental results on Twitter named entity recognition and sentence dependency tagging tasks show that our method outperforms spanning tree based dual decomposition.

2013

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Disfluency Detection Using Multi-step Stacked Learning
Xian Qian | Yang Liu
Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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Fast Joint Compression and Summarization via Graph Cuts
Xian Qian | Yang Liu
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

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Branch and Bound Algorithm for Dependency Parsing with Non-local Features
Xian Qian | Yang Liu
Transactions of the Association for Computational Linguistics, Volume 1

Graph based dependency parsing is inefficient when handling non-local features due to high computational complexity of inference. In this paper, we proposed an exact and efficient decoding algorithm based on the Branch and Bound (B&B) framework where non-local features are bounded by a linear combination of local features. Dynamic programming is used to search the upper bound. Experiments are conducted on English PTB and Chinese CTB datasets. We achieved competitive Unlabeled Attachment Score (UAS) when no additional resources are available: 93.17% for English and 87.25% for Chinese. Parsing speed is 177 words per second for English and 97 words per second for Chinese. Our algorithm is general and can be adapted to non-projective dependency parsing or other graphical models.

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Using Supervised Bigram-based ILP for Extractive Summarization
Chen Li | Xian Qian | Yang Liu
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

2012

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Joint Chinese Word Segmentation, POS Tagging and Parsing
Xian Qian | Yang Liu
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

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A Two-step Approach to Sentence Compression of Spoken Utterances
Dong Wang | Xian Qian | Yang Liu
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

2010

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Joint Training and Decoding Using Virtual Nodes for Cascaded Segmentation and Tagging Tasks
Xian Qian | Qi Zhang | Yaqian Zhou | Xuanjing Huang | Lide Wu
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing

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2D Trie for Fast Parsing
Xian Qian | Qi Zhang | Xuanjing Huang | Lide Wu
Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)

2008

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CRF-based Hybrid Model for Word Segmentation, NER and even POS Tagging
Zhiting Xu | Xian Qian | Yuejie Zhang | Yaqian Zhou
Proceedings of the Sixth SIGHAN Workshop on Chinese Language Processing