3 papers
cs.CR2026
Security in LLM-as-a-Judge: A Comprehensive SoK
Aiman Al Masoud, Antony Anju, Marco Arazzi +6
LLM-as-a-Judge (LaaJ) is a novel paradigm in which powerful language models are used to assess the quality, safety, or correctness of generated outputs. While this paradigm has sig…
cs.LG2025
Privacy Preserving and Robust Aggregation for Cross-Silo Federated Learning in Non-IID Settings
Marco Arazzi, Mert Cihangiroglu, Antonino Nocera
Federated Averaging remains the most widely used aggregation strategy in federated learning due to its simplicity and scalability. However, its performance degrades significantly i…
cs.CR2025
Secure Federated Data Distillation
Marco Arazzi, Mert Cihangiroglu, Serena Nicolazzo +1
Dataset Distillation (DD) is a powerful technique for reducing large datasets into compact, representative synthetic datasets, accelerating Machine Learning training. However, trad…