Fabrizio Frasca

44 papers A* 11B 1Journal 28Unranked 4
YearRankTypeTitle / Venue / Authors
2026 A* conf
Beyond Next Token Probabilities: Learnable, Fast Detection of Hallucinations and Data Contamination on LLM Output Distributions.
AAAI
Guy Bar-Shalom, Fabrizio Frasca, Derek Lim, Yoav Gelberg, Yftah Ziser, Ran El-Yaniv, Gal Chechik, Haggai Maron
2025 A* conf
Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality.
ICML
Joshua Southern, Yam Eitan, Guy Bar-Shalom, Michael M. Bronstein, Haggai Maron, Fabrizio Frasca
2025 J jnl
Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality.
CoRR
Joshua Southern, Yam Eitan, Guy Bar-Shalom, Michael M. Bronstein, Haggai Maron, Fabrizio Frasca
2025 J jnl
Beyond Token Probes: Hallucination Detection via Activation Tensors with ACT-ViT.
CoRR
Guy Bar-Shalom, Fabrizio Frasca, Yaniv Galron, Yftah Ziser, Haggai Maron
2025 J jnl
FS-KAN: Permutation Equivariant Kolmogorov-Arnold Networks via Function Sharing.
CoRR
Ran Elbaz, Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron
2025 J jnl
GraphBench: Next-generation graph learning benchmarking.
CoRR
Timo Stoll, Chendi Qian, Ben Finkelshtein, Ali Parviz, Darius Weber, Fabrizio Frasca, Hadar Shavit, Antoine Siraudin, Arman Mielke, Marie Anastacio, Erik Müller, Maya Bechler-Speicher, Michael M. Bronstein, Mikhail Galkin, Holger H. Hoos, Mathias Niepert, Bryan Perozzi, Jan Tönshoff, Christopher Morris
2025 J jnl
Learning on LLM Output Signatures for gray-box LLM Behavior Analysis.
CoRR
Guy Bar-Shalom, Fabrizio Frasca, Derek Lim, Yoav Gelberg, Yftah Ziser, Ran El-Yaniv, Gal Chechik, Haggai Maron
2025 J jnl
Lost in Serialization: Invariance and Generalization of LLM Graph Reasoners.
CoRR
Daniel Herbst, Lea Karbevska, Divyanshu Kumar, Akanksha Ahuja, Fatemeh Gholamzadeh Nasrabadi, Fabrizio Frasca
2025 J jnl
Neural Message-Passing on Attention Graphs for Hallucination Detection.
CoRR
Fabrizio Frasca, Guy Bar-Shalom, Yftah Ziser, Haggai Maron
2025 J jnl
On The Expressive Power of GNN Derivatives.
CoRR
Yam Eitan, Moshe Eliasof, Yoav Gelberg, Fabrizio Frasca, Guy Bar-Shalom, Haggai Maron
2025 — conf
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks.
ICML (Position Papers)
Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Müller, Jan Tönshoff, Antoine Siraudin, Viktor Zaverkin, Michael M. Bronstein, Mathias Niepert, Bryan Perozzi, Mikhail Galkin, Christopher Morris
2025 J jnl
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks.
CoRR
Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Müller, Jan Tönshoff, Antoine Siraudin, Viktor Zaverkin, Michael M. Bronstein, Mathias Niepert, Bryan Perozzi, Mikhail Galkin, Christopher Morris
2025 A* conf
Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity.
ICLR
Yam Eitan, Yoav Gelberg, Guy Bar-Shalom, Fabrizio Frasca, Michael M. Bronstein, Haggai Maron
2025 J jnl
Understanding and Improving Laplacian Positional Encodings For Temporal GNNs.
CoRR
Yaniv Galron, Fabrizio Frasca, Haggai Maron, Eran Treister, Moshe Eliasof
2025 — conf
Understanding and Improving Laplacian Positional Encodings for Temporal GNNs.
ECML/PKDD (2)
Yaniv Galron, Fabrizio Frasca, Haggai Maron, Eran Treister, Moshe Eliasof
2024 A* conf
A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening.
NeurIPS
Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron
2024 J jnl
A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening.
CoRR
Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron
2024 J jnl
Future Directions in Foundations of Graph Machine Learning.
CoRR
Christopher Morris, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Fabrizio Frasca, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka
2024 A* conf
Position: Future Directions in the Theory of Graph Machine Learning.
ICML
Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka
2024 J jnl
Topological Blind Spots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity.
CoRR
Yam Eitan, Yoav Gelberg, Guy Bar-Shalom, Fabrizio Frasca, Michael M. Bronstein, Haggai Maron
2024 J jnl
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs.
CoRR
Fabrizio Frasca, Fabian Jogl, Moshe Eliasof, Matan Ostrovsky, Carola-Bibiane Schönlieb, Thomas Gärtner, Haggai Maron
2023 — conf
Edge Directionality Improves Learning on Heterophilic Graphs.
LoG
Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein
2023 J jnl
Edge Directionality Improves Learning on Heterophilic Graphs.
CoRR
Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein
2023 A* conf
Graph Neural Networks for Link Prediction with Subgraph Sketching.
ICLR
Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Yannick Hammerla, Michael M. Bronstein, Max Hansmire
2023 A* conf
Graph Positional Encoding via Random Feature Propagation.
ICML
Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron
2023 J jnl
Graph Positional Encoding via Random Feature Propagation.
CoRR
Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron
2023 J jnl
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting.
IEEE Trans. Pattern Anal. Mach. Intell.
Giorgos Bouritsas, Fabrizio Frasca, Stefanos Zafeiriou, Michael M. Bronstein
2022 J jnl
Accurate and highly interpretable prediction of gene expression from histone modifications.
BMC Bioinform.
Fabrizio Frasca, Matteo Matteucci, Michele Leone, Marco J. Morelli, Marco Masseroli
2022 A* conf
Equivariant Subgraph Aggregation Networks.
ICLR
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron
2022 J jnl
Graph Neural Networks for Link Prediction with Subgraph Sketching.
CoRR
Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Hammerla, Michael M. Bronstein, Max Hansmire
2022 A* conf
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries.
NeurIPS
Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron
2022 J jnl
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries.
CoRR
Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron
2021 J jnl
Equivariant Subgraph Aggregation Networks.
CoRR
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron
2021 A* conf
Weisfeiler and Lehman Go Cellular: CW Networks.
NeurIPS
Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yuguang Wang, Pietro Liò, Guido F. Montúfar, Michael M. Bronstein
2021 J jnl
Weisfeiler and Lehman Go Cellular: CW Networks.
CoRR
Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yu Guang Wang, Pietro Liò, Guido Montúfar, Michael M. Bronstein
2021 A* conf
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks.
ICML
Cristian Bodnar, Fabrizio Frasca, Yuguang Wang, Nina Otter, Guido F. Montúfar, Pietro Lió, Michael M. Bronstein
2021 J jnl
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks.
CoRR
Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montúfar, Pietro Liò, Michael M. Bronstein
2020 J jnl
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting.
CoRR
Giorgos Bouritsas, Fabrizio Frasca, Stefanos Zafeiriou, Michael M. Bronstein
2020 J jnl
SIGN: Scalable Inception Graph Neural Networks.
CoRR
Emanuele Rossi, Fabrizio Frasca, Ben Chamberlain, Davide Eynard, Michael M. Bronstein, Federico Monti
2020 J jnl
Temporal Graph Networks for Deep Learning on Dynamic Graphs.
CoRR
Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca, Davide Eynard, Federico Monti, Michael M. Bronstein
2019 J jnl
Fake News Detection on Social Media using Geometric Deep Learning.
CoRR
Federico Monti, Fabrizio Frasca, Davide Eynard, Damon Mannion, Michael M. Bronstein
2019 J jnl
Learning interpretable disease self-representations for drug repositioning.
CoRR
Fabrizio Frasca, Diego Galeano, Guadalupe Gonzalez, Ivan Laponogov, Kirill A. Veselkov, Alberto Paccanaro, Michael M. Bronstein
2018 — conf
Exposing and Characterizing Subpopulations of Distinctly Regulated Genes by K-Plane Regression.
CIBB
Fabrizio Frasca, Matteo Matteucci, Marco J. Morelli, Marco Masseroli
2018 B conf
Modeling Gene Transcriptional Regulation by Means of Hyperplanes Genetic Clustering.
IJCNN
Fabrizio Frasca, Matteo Matteucci, Marco Masseroli, Marco J. Morelli