Federico Barbero

According to our database, Federico Barbero authored at least 16 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

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, April, 2025

Interpreting the Repeated Token Phenomenon in Large Language Models.

Itay Yona, Ilia Shumailov, Jamie Hayes, Federico Barbero, Yossi Gandelsman

CoRR, March, 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, Michael M. Bronstein, Pierre Vandergheynst

CoRR, February, 2025

Round and Round We Go! What makes Rotary Positional Encodings useful?

Federico Barbero, Alex Vitvitskyi, Christos Perivolaropoulos, Razvan Pascanu, Petar Velickovic

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Bundle Neural Network for message diffusion on graphs.

Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification.

Benedict Aaron Tjandra, Federico Barbero, Michael M. Bronstein

CoRR, 2024

softmax is not enough (for sharp out-of-distribution).

Petar Velickovic, Christos Perivolaropoulos, Federico Barbero, Razvan Pascanu

CoRR, 2024

Bundle Neural Networks for message diffusion on graphs.

Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Locality-Aware Graph Rewiring in GNNs.

Federico Barbero, Ameya Velingker, Amin Saberi, Michael M. Bronstein, Francesco Di Giovanni

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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

Proceedings of the International Conference on Machine Learning, 2023

Latent Graph Inference using Product Manifolds.

Haitz Sáez de Ocáriz Borde, Anees Kazi, Federico Barbero, Pietro Liò

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Graph Neural Network Expressivity and Meta-Learning for Molecular Property Regression.

Haitz Sáez de Ocáriz Borde, Federico Barbero

CoRR, 2022

Sheaf Neural Networks with Connection Laplacians.

Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Michael M. Bronstein, Petar Velickovic, Pietro Liò

Proceedings of the Topological, 2022

Transcending TRANSCEND: Revisiting Malware Classification in the Presence of Concept Drift.

Federico Barbero, Feargus Pendlebury, Fabio Pierazzi, Lorenzo Cavallaro

Proceedings of the 43rd IEEE Symposium on Security and Privacy, 2022

2020

Transcending Transcend: Revisiting Malware Classification with Conformal Evaluation.

Federico Barbero, Feargus Pendlebury, Fabio Pierazzi, Lorenzo Cavallaro

CoRR, 2020