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Found 8 papers, 5 papers with code
The Hidden Attention of Mamba Models
The Mamba layer offers an efficient selective state space model (SSM) that is highly effective in modeling multiple domains, including NLP, long-range sequence processing, and computer vision.
Degree-based stratification of nodes in Graph Neural Networks
Here, we propose a different approach that is based on a stratification of the graph nodes.
Centered Self-Attention Layers
The self-attention mechanism in transformers and the message-passing mechanism in graph neural networks are repeatedly applied within deep learning architectures.
XAI for Transformers: Better Explanations through Conservative Propagation
Transformers have become an important workhorse of machine learning, with numerous applications.
Video and Text Matching with Conditioned Embeddings
Traditionally video and text matching is done by learning a shared embedding space and the encoding of one modality is independent of the other.
Explainability Guided Multi-Site COVID-19 CT Classification
Radiologist examination of chest CT is an effective way for screening COVID-19 cases.
Weakly Supervised Recovery of Semantic Attributes
We consider the problem of the extraction of semantic attributes, supervised only with classification labels.
Visualization of Supervised and Self-Supervised Neural Networks via Attribution Guided Factorization
However, as we show, these methods are limited in their ability to identify the support for alternative classifications, an effect we name {\em the saliency bias} hypothesis.
