Aug 23, 2020 · This paper develops the Correlation Networks (CorNet) architec- ture for the extreme multi-label text classification (XMTC) task, where the ...
Aug 20, 2020 · This paper develops the Correlation Networks (CorNet) architecture for the extreme multi-label text classification (XMTC) task, ...
This paper develops the Correlation Networks (CorNet) architecture for the extreme multi-label text classification (XMTC) task, where the objective is to ...
Correlation Networks for Extreme Multi-label Text Classification.pdf ...
The Correlation Networks (CorNet) architecture for the extreme multi-label text classification (XMTC) task, where the objective is to tag an input text ...
The TAE focuses on capturing topic information when modeling the sequence semantics and, therefore, does not use a pre-trained model to assure fair ...
This project develops the Correlation Networks (CorNet) architecture for the extreme multi-label text classification (XMTC) task, where the objective is to tag ...
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Sep 30, 2024 · This paper proposes a model of Label Attention and Correlation Networks (LACN) to address the challenges of classifying multi-label text and enhance ...
Feb 10, 2024 · We propose a novel model called TLC-XML, ie, a Transformer with label correlation for extreme multi-label text classification.
Sparse local embeddings for extreme multi-label classification. In Advances in neural information processing systems. 730--738. Kush Bhatia Himanshu Jain ...