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Long-tailed relation classification is a challenging problem as the head classes may dominate the training phase, thereby leading to the deterioration of the tail performance.
Long-tail relation extraction via knowledge graph embeddings and graph convolution networks
Ningyu Zhang, Shumin Deng, Zhanlin Sun, Guanying Wang, Xi Chen, Wei Zhang, and Huajun Chen. 2019b · 1903
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Decoupling representation and classifier for long-tailed recognition
Bingyi Kang, Saining Xie, Marcus Rohrbach, Zhicheng Yan, Albert Gordo, Jiashi Feng, and Yannis Kalantidis. 2020 · 1910
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Xiaoya Li, Xiaofei Sun, Yuxian Meng, Junjun Liang, Fei Wu, and Jiwei Li. 2019 · 1911
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To balance or not to balance: A simple-yet-effective approach for learning with long-tailed distributions
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Ningyu Zhang, Luoqiu Li, Shumin Deng, Haiyang Yu, Xu Cheng, Wei Zhang, and Huajun Chen. 2020b · 2009
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Attention-based capsule networks with dynamic routing for relation extraction
Ningyu Zhang, Shumin Deng, Zhanling Sun, Xi Chen, Wei Zhang, and Huajun Chen. 2018 · 2018
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