3 papers
cs.AI2026
The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning
Agnese Chiatti, Michael Cochez, Cristina Cornelio +14
Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention. They complement the data-intensive statistical approaches of neural n…
cs.LG2024
Toward a Realistic Benchmark for Out-of-Distribution Detection
Pietro Recalcati, Fabio Garcea, Luca Piano +2
Deep neural networks are increasingly used in a wide range of technologies and services, but remain highly susceptible to out-of-distribution (OOD) samples, that is, drawn from a d…
cs.CV2024
HOLMES: HOLonym-MEronym based Semantic inspection for Convolutional Image Classifiers
Francesco Dibitonto, Fabio Garcea, André Panisson +2
Convolutional Neural Networks (CNNs) are nowadays the model of choice in Computer Vision, thanks to their ability to automatize the feature extraction process in visual tasks. Howe…