DeepAI AI Chat
Log In Sign Up

A Novel Perspective to Look At Attention: Bi-level Attention-based Explainable Topic Modeling for News Classification

by   Dairui Liu, et al.

Many recent deep learning-based solutions have widely adopted the attention-based mechanism in various tasks of the NLP discipline. However, the inherent characteristics of deep learning models and the flexibility of the attention mechanism increase the models' complexity, thus leading to challenges in model explainability. In this paper, to address this challenge, we propose a novel practical framework by utilizing a two-tier attention architecture to decouple the complexity of explanation and the decision-making process. We apply it in the context of a news article classification task. The experiments on two large-scaled news corpora demonstrate that the proposed model can achieve competitive performance with many state-of-the-art alternatives and illustrate its appropriateness from an explainability perspective.


Multi-Layer Attention-Based Explainability via Transformers for Tabular Data

We propose a graph-oriented attention-based explainability method for ta...

Explainable Graph Pyramid Autoformer for Long-Term Traffic Forecasting

Accurate traffic forecasting is vital to an intelligent transportation s...

Deep Features Analysis with Attention Networks

Deep neural network models have recently draw lots of attention, as it c...

Staying True to Your Word: (How) Can Attention Become Explanation?

The attention mechanism has quickly become ubiquitous in NLP. In additio...

Attention vs non-attention for a Shapley-based explanation method

The field of explainable AI has recently seen an explosion in the number...

Attention-Based Prototypical Learning Towards Interpretable, Confident and Robust Deep Neural Networks

We propose a new framework for prototypical learning that bases decision...

A Concept-based Abstraction-Aggregation Deep Neural Network for Interpretable Document Classification

Using attention weights to identify information that is important for mo...