Abstract: This paper proposes a multi-label text classification algorithm based on causal relationships to address the current challenge of accurately capturing label correlations in multi-label text ...

Nov 3 (Reuters) - Artificial intelligence cloud startup Lambda said on Monday it has entered into a multi-billion-dollar agreement with Microsoft (MSFT.O), opens new tab to deploy tens of thousands of ...

Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language generation.

NeuralClassifier is designed for quick implementation of neural models for hierarchical multi-label classification task, which is more challenging and common in real-world scenarios. A salient feature ...

Abstract: Multi-label text classification involves assigning multiple relevant categories to a single text, enabling applications in academic indexing, medical diagnostics, and e-commerce. However, ...

LVMH held talks with Authentic Brands, WHP Global to sell Marc Jacobs - sources French luxury goods group recently offloaded some of its brands WSJ said deal for Marc Jacobs could be worth around $1 ...

In an era of rapidly growing multimedia data, the need for robust and efficient classification systems has become critical, specifically the identification of class names and poses or styles. This ...

This section reviews the development of rhetorical role labeling methods in legal texts, highlighting key advances from CRF models to deep learning, and explores neighborhood learning techniques for ...

[2019-06-24 20:44:44]: bert train_bert_multi_label.py [line:75] INFO initializing model Traceback (most recent call last): File "train_bert_multi_label.py", line 144, in main () File "train_bert_multi ...