Transcending Transcend: Revisiting Malware Classification with Conformal Evaluation. - Federico Barbero; Feargus Pendlebury; Fabio Pierazzi; Lorenzo Cavallaro (CoRR, 2020)

Transcending TRANSCEND: Revisiting Malware Classification in the Presence of Concept Drift. - Federico Barbero; Feargus Pendlebury; Fabio Pierazzi; Lorenzo Cavallaro (SP, 2022)

Sheaf Neural Networks with Connection Laplacians. - Federico Barbero; Cristian Bodnar; Haitz Sáez de Ocáriz Borde; Michael M. Bronstein; Petar Velickovic; Pietro Liò (TAG-ML, 2022)

Graph Neural Network Expressivity and Meta-Learning for Molecular Property Regression. - Haitz Sáez de Ocáriz Borde; Federico Barbero (CoRR, 2022)

Latent Graph Inference using Product Manifolds. - Haitz Sáez de Ocáriz Borde; Anees Kazi; Federico Barbero; Pietro Liò (ICLR, 2023)

On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology. - Francesco Di Giovanni; Lorenzo Giusti; Federico Barbero; Giulia Luise; Pietro Lio; Michael M. Bronstein (ICML, 2023)

Locality-Aware Graph Rewiring in GNNs. - Federico Barbero; Ameya Velingker; Amin Saberi; Michael M. Bronstein; Francesco Di Giovanni (ICLR, 2024)

Transformers need glasses! Information over-squashing in language tasks. - Federico Barbero; Andrea Banino; Steven Kapturowski; Dharshan Kumaran; João Guilherme Madeira Araújo; Oleksandr Vitvitskyi; Razvan Pascanu; Petar Velickovic (NeurIPS, 2024)

Bundle Neural Networks for message diffusion on graphs. - Jacob Bamberger; Federico Barbero; Xiaowen Dong 001; Michael M. Bronstein (CoRR, 2024)

softmax is not enough (for sharp out-of-distribution). - Petar Velickovic; Christos Perivolaropoulos; Federico Barbero; Razvan Pascanu (CoRR, 2024)

Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification. - Benedict Aaron Tjandra; Federico Barbero; Michael M. Bronstein (CoRR, 2024)

Bundle Neural Network for message diffusion on graphs. - Jacob Bamberger; Federico Barbero; Xiaowen Dong 001; Michael M. Bronstein (ICLR, 2025)

Round and Round We Go! What makes Rotary Positional Encodings useful? - Federico Barbero; Alex Vitvitskyi; Christos Perivolaropoulos; Razvan Pascanu; Petar Velickovic (ICLR, 2025)

On Vanishing Gradients, Over-Smoothing, and Over-Squashing in GNNs: Bridging Recurrent and Graph Learning. - Alvaro Arroyo; Alessio Gravina; Benjamin Gutteridge; Federico Barbero; Claudio Gallicchio; Xiaowen Dong 001; Michael M. Bronstein; Pierre Vandergheynst (CoRR, 2025)

Interpreting the Repeated Token Phenomenon in Large Language Models. - Itay Yona; Ilia Shumailov; Jamie Hayes; Federico Barbero; Yossi Gandelsman (CoRR, 2025)

Why do LLMs attend to the first token? - Federico Barbero; Alvaro Arroyo; Xiangming Gu; Christos Perivolaropoulos; Michael M. Bronstein; Petar Velickovic; Razvan Pascanu (CoRR, 2025)