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Exploiting label hierarchies has become a promising approach to tackling the zero-shot multi-label text classification (ZS-MTC) problem.
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Mastering the game of go with deep neural networks and tree search
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Hierarchical multi-label classification networks
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Large-scale multi-label text classification on EU legislation
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Ml-net: multi-label classification of biomedical texts with deep neural networks
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Yikun Xian, Zuohui Fu, S Muthukrishnan, Gerard De Melo, and Yongfeng Zhang. 2019 · 2019
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Ehr coding with multi-scale feature attention and structured knowledge graph propagation
Xiancheng Xie, Yun Xiong, Philip S Yu, and Yangyong Zhu. 2019 · 2019
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Benchmarking zero-shot text classification: Datasets, evaluation and entailment approach
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A shared multi-attention framework for multi-label zero-shot learning
Dat Huynh and Ehsan Elhamifar. 2020 · 2020
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Zero-shot text classification via reinforced self-training
Zhiquan Ye, Yuxia Geng, Jiaoyan Chen, Jingmin Chen, Xiaoxiao Xu, SuHang Zheng, Feng Wang, Jun Zhang, and Huajun Chen. 2020 · 2020
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