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By Hao Guo, Kang Zheng, Xiaochuan Fan, Hongkai Yu, Song Wang

Subfields: Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Natural Language Processing

1. Adriana Romero
2. Fei Wu
3. Gunhee Kim
4. Ivor Wai-Hung Tsang
5. Jinseo Jeong
6. Xi Li
7. Luis Villaseñor Pineda
8. Amaia Salvador

Citations in the corpus

• Elucidating image-to-set prediction: An analysis of models, losses and datasets (2019, methodology): “2019 [16] ResNet-101 3 82783 n/a 40504 73.”
• Imbalanced Continual Learning with Partitioning Reservoir Sampling (2020, methodology): “Recently, recurrent approaches [84,87] and attention-based methods [97,33] are proposed to correlate the labels during predictions.”
• FcaNet: Frequency Channel Attention Networks (2020, methodology): “Besides these works, many methods try to extend the attention mechanism to specific tasks, like multi-label clas-sification [14], saliency detection [44], visual explanation [10], and super-resolution [43].”
• The Emerging Trends of Multi-Label Learning (2020, background): “[141] finds the consistency of attention regions of CNN classifiers under many LIU ETAL.”