Yong Jiang

Proceedings of the 16th International Conference on Parsing Technologies and the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies, 2020

AIN: Fast and Accurate Sequence Labeling with Approximate Inference Network.

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[DOI]

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

An Investigation of Potential Function Designs for Neural CRF.

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[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Adversarial Attack and Defense of Structured Prediction Models.

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[DOI]

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

More Embeddings, Better Sequence Labelers?

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[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Second-Order Unsupervised Neural Dependency Parsing.

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[DOI]

Proceedings of the 28th International Conference on Computational Linguistics, 2020

A Survey of Unsupervised Dependency Parsing.

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[DOI]

Proceedings of the 28th International Conference on Computational Linguistics, 2020

Structure-Level Knowledge Distillation For Multilingual Sequence Labeling.

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[DOI]

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

An Empirical Comparison of Unsupervised Constituency Parsing Methods.

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[DOI]

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Learning and evaluation of latent dependency forest models.

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[DOI]

Yang Zhou

Neural Comput. Appl., 2019

Lexicalized Neural Unsupervised Dependency Parsing.

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[DOI]

Neurocomputing, 2019

Projective Latent Dependency Forest Models.

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[DOI]

Yang Zhou

IEEE Access, 2019

A Regularization-based Framework for Bilingual Grammar Induction.

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[DOI]

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Multilingual Grammar Induction with Continuous Language Identification.

[BibT_eX]

[DOI]

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Enhancing Unsupervised Generative Dependency Parser with Contextual Information.

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[DOI]

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Bidirectional Transition-Based Dependency Parsing.

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[DOI]

Yunzhe Yuan

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Maximum A Posteriori Inference in Sum-Product Networks.

[BibT_eX]

[DOI]

Jun Mei

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Semi-supervised Structured Prediction with Neural CRF Autoencoder.

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[DOI]

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Combining Generative and Discriminative Approaches to Unsupervised Dependency Parsing via Dual Decomposition.

[BibT_eX]

[DOI]

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Dependency Grammar Induction with Neural Lexicalization and Big Training Data.

[BibT_eX]

[DOI]

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

CRF Autoencoder for Unsupervised Dependency Parsing.

[BibT_eX]

[DOI]

Jiong Cai

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Latent Dependency Forest Models.

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[DOI]

Shanbo Chu

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Unsupervised Neural Dependency Parsing.

[BibT_eX]

[DOI]