8 citations · 10 across the 5 of their papers we have counts for
5 papers
CEnt: An Entropy-based Model-agnostic Explainability Framework to Contrast Classifiers' Decisions
Julia El Zini, Mohammad Mansour, Mariette Awad
Current interpretability methods focus on explaining a particular model's decision through present input features. Such methods do not inform the user of the sufficient conditions…
Beyond Model Interpretability: On the Faithfulness and Adversarial Robustness of Contrastive Textual Explanations
Julia El Zini, Mariette Awad
Contrastive explanation methods go beyond transparency and address the contrastive aspect of explanations. Such explanations are emerging as an attractive option to provide actiona…
On the Evaluation of the Plausibility and Faithfulness of Sentiment Analysis Explanations
Julia El Zini, Mohamad Mansour, Basel Mousi +1
Current Explainable AI (ExAI) methods, especially in the NLP field, are conducted on various datasets by employing different metrics to evaluate several aspects. The lack of a comm…
An Optimized and Energy-Efficient Parallel Implementation of Non-Iteratively Trained Recurrent Neural Networks
Julia El Zini, Yara Rizk, Mariette Awad
Recurrent neural networks (RNN) have been successfully applied to various sequential decision-making tasks, natural language processing applications, and time-series predictions. S…
Change your singer: a transfer learning generative adversarial framework for song to song conversion
Rema Daher, Mohammad Kassem Zein, Julia El Zini +2
Have you ever wondered how a song might sound if performed by a different artist? In this work, we propose SCM-GAN, an end-to-end non-parallel song conversion system powered by gen…