Jianhai Zhang
2019
Simple and Effective Text Matching with Richer Alignment Features
Runqi Yang
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Jianhai Zhang
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Xing Gao
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Feng Ji
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Haiqing Chen
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
In this paper, we present a fast and strong neural approach for general purpose text matching applications. We explore what is sufficient to build a fast and well-performed text matching model and propose to keep three key features available for inter-sequence alignment: original point-wise features, previous aligned features, and contextual features while simplifying all the remaining components. We conduct experiments on four well-studied benchmark datasets across tasks of natural language inference, paraphrase identification and answer selection. The performance of our model is on par with the state-of-the-art on all datasets with much fewer parameters and the inference speed is at least 6 times faster compared with similarly performed ones.
2016
DUTIR in BioNLP-ST 2016: Utilizing Convolutional Network and Distributed Representation to Extract Complicate Relations
Honglei Li
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Jianhai Zhang
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Jian Wang
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Hongfei Lin
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Zhihao Yang
Proceedings of the 4th BioNLP Shared Task Workshop
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Co-authors
- Honglei Li 1
- Jian Wang 1
- Hongfei Lin 1
- Zhihao Yang 1
- Runqi Yang 1
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