4 papers
Verifying Machine Unlearning with Explainable AI
Àlex Pujol Vidal, Anders S. Johansen, Mohammad N. S. Jahromi +3
We investigate the effectiveness of Explainable AI (XAI) in verifying Machine Unlearning (MU) within the context of harbor front monitoring, focusing on data privacy and regulatory…
SIDU-TXT: An XAI Algorithm for NLP with a Holistic Assessment Approach
Mohammad N. S. Jahromi, Satya. M. Muddamsetty, Asta Sofie Stage Jarlner +3
Explainable AI (XAI) aids in deciphering 'black-box' models. While several methods have been proposed and evaluated primarily in the image domain, the exploration of explainability…
Learning-based Monocular 3D Reconstruction of Birds: A Contemporary Survey
Seyed Mojtaba Marvasti-Zadeh, Mohammad N. S. Jahromi, Javad Khaghani +3
In nature, the collective behavior of animals, such as flying birds is dominated by the interactions between individuals of the same species. However, the study of such behavior am…
Visual explanation of black-box model: Similarity Difference and Uniqueness (SIDU) method
Satya M. Muddamsetty, Mohammad N. S. Jahromi, Andreea E. Ciontos +2
Explainable Artificial Intelligence (XAI) has in recent years become a well-suited framework to generate human understandable explanations of "black-box" models. In this paper, a n…