Filippo Betello

Orcid: 0009-0006-0945-9688

According to our database1, Filippo Betello authored at least 16 papers between 2023 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
PONTE: Personalized Orchestration for Natural Language Trustworthy Explanations.
CoRR, March, 2026

Your LLM Has a Passport: Investigating Brand Origin Geographic Bias in E-Commerce Rankings.
Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency, 2026

Iterative Reranking as a Compute-Scaling Method for LLM-Based Rankers.
Proceedings of the Advances in Information Retrieval, 2026

2025
Demystifying Sequential Recommendations: Counterfactual Explanations via Genetic Algorithms.
CoRR, August, 2025

One Search Fits All: Pareto-Optimal Eco-Friendly Model Selection.
CoRR, May, 2025

A Reproducible Analysis of Sequential Recommender Systems.
IEEE Access, 2025

Are Convolutional Sequential Recommender Systems Still Competitive? Introducing New Models and Insights.
Proceedings of the International Joint Conference on Neural Networks, 2025

Caser+ and CosRec+: Closing the Gap Between CNNs and Attention Models in SRS.
Proceedings of the 15th Italian Information Retrieval Workshop (IIR 2025), 2025

QPP-RA: Aggregating Large Language Model Rankings.
Proceedings of the 2025 International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval, 2025

2024
Attention-map augmentation for hypercomplex breast cancer classification.
Pattern Recognit. Lett., 2024

Learning visual stimulus-evoked EEG manifold for neural image classification.
Neurocomputing, 2024

The Role of Fake Users in Sequential Recommender Systems.
Proceedings of the Workshop Design, 2024

Finite Rank-Biased Overlap (FRBO): A New Measure for Stability in Sequential Recommender Systems.
Proceedings of the 14th Italian Information Retrieval Workshop, 2024

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

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

Deep Image Inpainting to Support Endoscopic Procedures.
Proceedings of the 31st Mediterranean Conference on Control and Automatio, 2023


  Loading...