18 papers
TrustErase: Auditable Instant Machine Unlearning with Passport-Embedded Representations
Rutger Hendrix, Leonardo G. Russo, Concetto Spampinato +2
The demand for privacy-compliant AI has amplified the need for machine unlearning; yet, existing retraining or distillation-based methods remain unverifiable and computationally co…
A Multi-Center Benchmark for Abdominal Disease Diagnosis and Report Generation from Non-Contrast CT
Mariam Elbakry, Aliaa Sayed Sheha, Salma Hassan Tantawy +5
Multiphasic contrast-enhanced CT (CECT) is widely used for abdominal lesion characterization, yet it carries inherent risks of contrast-induced nephropathy, escalates acquisition b…
Cyst-X: A Multi-Center MRI Benchmark and Federated Learning Framework for Malignancy-Risk Stratification of Pancreatic Cystic Neoplasm
Hongyi Pan, Gorkem Durak, Elif Keles +27
Pancreatic cancer is projected to be the second-deadliest cancer by 2030, making early detection critical. Intraductal papillary mucinous neoplasms (IPMNs), key cancer precursors,…
PERL: Parameter Efficient Reasoning in CLIP Latent Space
Simone Carnemolla, Salvatore Calcagno, Daniela Giordano +2
Contrastively trained vision-language models such as CLIP provide strong zero-shot transfer by aligning images and text in a shared embedding space. However, adapting these models…
OCCAM: Open-set Causal Concept explAnation and Ontology induction for black-box vision Models
Chiara Maria Russo, Simone Carnemolla, Simone Palazzo +3
Interpreting the decisions of deep image classifiers remains challenging, particularly in black-box settings where model internals are inaccessible. We introduce OCCAM, a framework…
Global-Local Feature Decoding with Adapter-Guided SAMv2 for Salient Object Detection
Morteza Moradi, Mohammad Moradi, Simone Palazzo +2
Salient Object Detection (SOD) remains an essential yet underexplored task in the era of large-scale vision models. Although foundation models like SAM exhibit strong generalizatio…