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20172026
most citedElliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

102 citations · 384 across the 37 of their papers we have counts for

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Showing 2026Show all

5 papers · 1 filter

stat.ML2026

The Representational Limit of Scalar Interactions: An Interventional Decomposition

Potito Aghilar, Sabino Roccotelli, Stanislao Fidanza +3

Signed pairwise interaction scores fundamentally conflate uniqueness (U), redundancy (R), and synergy (S). We prove this on a minimal 3-way XOR structural causal model: faithful in…

cs.AI2026

The EpisTwin: A Knowledge Graph-Grounded Neuro-Symbolic Architecture for Personal AI

Giovanni Servedio, Potito Aghilar, Alessio Mattiace +6

Personal Artificial Intelligence is currently hindered by the fragmentation of user data across isolated silos. While Retrieval-Augmented Generation offers a partial remedy, its re…

cs.AI2026★ 1 cited

WarpRec: Unifying Academic Rigor and Industrial Scale for Responsible, Reproducible, and Efficient Recommendation

Marco Avolio, Potito Aghilar, Sabino Roccotelli +9

Innovation in Recommender Systems is currently impeded by a fractured ecosystem, where researchers must choose between the ease of in-memory experimentation and the costly, complex…

cs.AI2026

RUVA: Personalized Transparent On-Device Graph Reasoning

Gabriele Conte, Alessio Mattiace, Gianni Carmosino +6

The Personal AI landscape is currently dominated by "Black Box" Retrieval-Augmented Generation. While standard vector databases offer statistical matching, they suffer from a funda…

cs.IR2026

Exploring Diversity, Novelty, and Popularity Bias in ChatGPT's Recommendations

Dario Di Palma, Giovanni Maria Biancofiore, Vito Walter Anelli +2

ChatGPT has emerged as a versatile tool, demonstrating capabilities across diverse domains. Given these successes, the Recommender Systems (RSs) community has begun investigating i…