Jie Xu


2019

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Uncover the Ground-Truth Relations in Distant Supervision: A Neural Expectation-Maximization Framework
Junfan Chen | Richong Zhang | Yongyi Mao | Hongyu Guo | Jie Xu
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Distant supervision for relation extraction enables one to effectively acquire structured relations out of very large text corpora with less human efforts. Nevertheless, most of the prior-art models for such tasks assume that the given text can be noisy, but their corresponding labels are clean. Such unrealistic assumption is contradictory with the fact that the given labels are often noisy as well, thus leading to significant performance degradation of those models on real-world data. To cope with this challenge, we propose a novel label-denoising framework that combines neural network with probabilistic modelling, which naturally takes into account the noisy labels during learning. We empirically demonstrate that our approach significantly improves the current art in uncovering the ground-truth relation labels.

2015

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Chinese CogBank: Where to See the Cognitive Features of Chinese Words
Bin Li | Xiaopeng Bai | Siqi Yin | Jie Xu
Proceedings of the Third Workshop on Metaphor in NLP

2003

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Focus-Marking in Chinese and Malay : A Comparative Perspective
Jie Xu
Proceedings of the 17th Pacific Asia Conference on Language, Information and Computation

1998

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Proceedings of the 12th Pacific Asia Conference on Language, Information and Computation
Jin Guo | Kim Teng Lua | Jie Xu
Proceedings of the 12th Pacific Asia Conference on Language, Information and Computation

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Grammatical Devices in the Processing of [+Wh] and [+Focus]
Jie Xu
Proceedings of the 12th Pacific Asia Conference on Language, Information and Computation