Reproducibility Analysis of Recommender Systems relying on Visual Features: traps, pitfalls, and countermeasures. - Pasquale Lops; Elio Musacchio; Cataldo Musto; Marco Polignano; Antonio Silletti; Giovanni Semeraro (RecSys, 2023)

ClayRS: An end-to-end framework for reproducible knowledge-aware recommender systems. - Pasquale Lops; Marco Polignano; Cataldo Musto; Antonio Silletti; Giovanni Semeraro (Inf. Syst., 2023)

Reproducibility of LLM-based Recommender Systems: the Case Study of P5 Paradigm. - Pasquale Lops; Antonio Silletti; Marco Polignano; Cataldo Musto; Giovanni Semeraro (RecSys, 2024)