5.2k citations
- SupélecFR441 papers
- Shandong University of Political Science and LawCN440 papers
- New York UniversityUS44 papers
- Dalle Molle Institute for Artificial Intelligence ResearchCH38 papers
- Princeton UniversityUS15 papers
- Google (United States)US13 papers
- Courant Institute of Mathematical SciencesUS11 papers
- Meta (Israel)IL11 papers
- Politecnico di TorinoIT11 papers
- ETH ZurichCH9 papers
- Massachusetts Institute of TechnologyUS8 papers
- University of California, BerkeleyUS8 papers
516 papers
Predicting, Evaluating, and Explaining Top Misinformation Spreaders via Archetypal User Behavior
Enrico Verdolotti, Luca Luceri, Silvia Giordano
The spread of misinformation on social networks poses a significant challenge to online communities and society at large. Not all users contribute equally to this phenomenon: a sma…
Thinking Fast, Thinking Slow: Adaptive Multimodal Transformer-based Sensor Fusion for Depth Estimation on Ultra-low-power MCUs
Luca Crupi, Lorenzo Lamberti, Giovanni Badaracco +3
Artificial intelligence (AI)-based multimodal sensor fusion is a relevant topic gaining ever more traction across ultra-low-power (ULP) embedded and cyber-physical systems, as it i…
Improving Autonomous Nano-drones Performance via Automated End-to-End Optimization and Deployment of DNNs
Vlad Niculescu, Lorenzo Lamberti, Francesco Conti +2
The evolution of energy-efficient ultra-low-power (ULP) parallel processors and the diffusion of convolutional neural networks (CNNs) are fueling the advent of autonomous driving n…
Policy-driven Conformal Prediction for Trustworthy QoT Estimation
Kiarash Rezaei, Omran Ayoub, Paolo Monti +1
We propose Conformal QoT, a policy-driven framework that combines statistically guaranteed QoT estimation with operational decision policies, enabling reliable lightpath-feasibilit…
Generative Explainability for Next-Generation Networks: LLM-Augmented XAI with Mutual Feature Interactions
Kiarash Rezaei, Omran Ayoub, Sebastian Troia +3
As artificial intelligence and machine learning (AI/ML) models become integral to network operations, their lack of transparency poses a significant barrier to operator trust. Exis…
FPLIER: Federated Pathway-Level Information Extractor
Daniele Malpetti, Christian Berchtold, Francesco Gualdi +3
In transcriptomics, gene-set-aware factorization methods such as the Pathway Level Information Extractor (PLIER) are most effective when trained on large, heterogeneous expression…