15 papers
Analyzing Shapley Additive Explanations to Understand Anomaly Detection Algorithm Behaviors and Their Complementarity
Jordan Levy, Paul Saves, Moncef Garouani +2
Unsupervised anomaly detection is a challenging problem due to the diversity of data distributions and the lack of labels. Ensemble methods are often adopted to mitigate these chal…
Interpretable and Explainable Surrogate Modeling for Simulations: A State-of-the-Art Survey and Perspectives on Explainable AI for Decision-Making
Pramudita Satria Palar, Paul Saves, Muhammad Daffa Robani +6
The simulation of complex systems increasingly relies on sophisticated but fundamentally opaque computational black-box simulators. Surrogate models play a central role in reducing…
IPatch: A Multi-Resolution Transformer Architecture for Robust Time-Series Forecasting
Aymane Harkati, Moncef Garouani, Olivier Teste +2
Accurate forecasting of multivariate time series remains challenging due to the need to capture both short-term fluctuations and long-range temporal dependencies. Transformer-based…
Fusion-CAM: Integrating Gradient and Region-Based Class Activation Maps for Robust Visual Explanations
Hajar Dekdegue, Moncef Garouani, Josiane Mothe +1
Interpreting the decision-making process of deep convolutional neural networks remains a central challenge in achieving trustworthy and transparent artificial intelligence. Explain…
Improving Neural Retrieval with Attribution-Guided Query Rewriting
Moncef Garouani, Josiane Mothe
Neural retrievers are effective but brittle: underspecified or ambiguous queries can misdirect ranking even when relevant documents exist. Existing approaches address this brittlen…
AmharicIR+Instr: A Two-Dataset Resource for Neural Retrieval and Instruction Tuning
Tilahun Yeshambel, Moncef Garouani, Josiane Mothe
Neural retrieval and GPT-style generative models rely on large, high-quality supervised data, which is still scarce for low-resource languages such as Amharic. We release an Amhari…