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In this project we trained personalized transformer models for news recommendation using adapters [similar to (IA)^3]. With layerwise relevancy propagation, we try to explain the recommendation to the user. Using a web interface and displaying word clouds, the user can be assigned to a “filter bubble”. This allows users to reflect on their behavior

Python 0.77% Jupyter Notebook 99.23%
ethical-ai explainable-ai layerwiserelevancepropogation personalisation transformer-adapters

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