Federico Siciliano

Orcid: 0000-0003-1339-6983

According to our database1, Federico Siciliano authored at least 14 papers between 2022 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
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PhD thesis 
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Links

Online presence:

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Bibliography

2024
The Power of Noise: Redefining Retrieval for RAG Systems.
CoRR, 2024

Investigating the Robustness of Sequential Recommender Systems Against Training Data Perturbations.
Proceedings of the Advances in Information Retrieval, 2024

2023
The CAESAR Project for the ASI Space Weather Infrastructure.
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Remote. Sens., January, 2023

Deep active learning for misinformation detection using geometric deep learning.
Online Soc. Networks Media, 2023

A graph neural network-based model with Out-of-Distribution Robustness for enhancing Antiretroviral Therapy Outcome Prediction for HIV-1.
CoRR, 2023

Adversarial Data Poisoning for Fake News Detection: How to Make a Model Misclassify a Target News without Modifying It.
CoRR, 2023

Investigating the Robustness of Sequential Recommender Systems Against Training Data Perturbations: an Empirical Study.
CoRR, 2023

Concept Distillation in Graph Neural Networks.
Proceedings of the Explainable Artificial Intelligence, 2023

Integrating Item Relevance in Training Loss for Sequential Recommender Systems.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Leveraging Inter-Rater Agreement for Classification in the Presence of Noisy Labels.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

RRAML: Reinforced Retrieval Augmented Machine Learning.
Proceedings of the Discussion Papers, 2023

2022
Encoding Concepts in Graph Neural Networks.
CoRR, 2022

NEWRON: A New Generalization of the Artificial Neuron to Enhance the Interpretability of Neural Networks.
Proceedings of the International Joint Conference on Neural Networks, 2022

FbMultiLingMisinfo: Challenging Large-Scale Multilingual Benchmark for Misinformation Detection.
Proceedings of the International Joint Conference on Neural Networks, 2022


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