3 citations · 6 across the 11 of their papers we have counts for
Showing 2026Show all
2 papers · 1 filter
cs.AI2026
Learning Symbolic Constraint Representations from Examples: A Neuro-Symbolic Approach
Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar +1
Learning user-defined concepts as constraint networks has been extensively studied in the constraint acquisition (CA) literature. However, existing approaches typically rely on int…
cs.CV2026
Energy-Regularized Spatial Masking: A Novel Approach to Enhancing Robustness and Interpretability in Vision Models
Tom Devynck, Bilal Faye, Djamel Bouchaffra +3
Deep convolutional neural networks achieve remarkable performance by exhaustively processing dense spatial feature maps, yet this brute-force strategy introduces significant comput…