Search Results for author:
Found 2 papers, 1 papers with code
Multi-Label Text Classification using Attention-based Graph Neural Network
The graph attention network uses a feature matrix and a correlation matrix to capture and explore the crucial dependencies between the labels and generate classifiers for the task.
Compositional Attention Networks for Interpretability in Natural Language Question Answering
Our experiments with 20 bAbI tasks demonstrate the value of MAC net as a data-efficient and interpretable architecture for Natural Language Question Answering.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
