Taking advantage of images and texts in recommender systems: semantics and explainability. - Pablo Pérez-Núñez (RecSys, 2020)

Towards explainable personalized recommendations by learning from users' photos. - Jorge Díez 001; Pablo Pérez-Núñez; Oscar Luaces; Beatriz Remeseiro; Antonio Bahamonde (Inf. Sci., 2020)

Improving recommender systems by encoding items and user profiles considering the order in their consumption history. - Pablo Pérez-Núñez; Oscar Luaces; Antonio Bahamonde; Jorge Díez 001 (Prog. Artif. Intell., 2020)

User encoding for clustering in very sparse recommender systems tasks. - Pablo Pérez-Núñez; Jorge Díez 001; Oscar Luaces; Antonio Bahamonde (Multim. Tools Appl., 2022)

Correction to: User encoding for clustering in very sparse recommender systems tasks. - Pablo Pérez-Núñez; Jorge Díez 001; Oscar Luaces; Antonio Bahamonde (Multim. Tools Appl., 2022)

Users' photos of items can reveal their tastes in a recommender system. - Pablo Pérez-Núñez; Jorge Díez 001; Oscar Luaces; Beatriz Remeseiro; Antonio Bahamonde (Inf. Sci., 2023)

All-in-one picture: visual summary of items in a recommender system. - Pablo Pérez-Núñez; Jorge Díez 001; Beatriz Remeseiro; Oscar Luaces; Antonio Bahamonde (Neural Comput. Appl., 2023)

A Self-Supervised Approach for Enhanced Feature Representations in Object Detection Tasks. - Santiago C. Vilabella; Pablo Pérez-Núñez; Beatriz Remeseiro (IJCNN, 2024)

Attention-inspired text-based recommender system with explanatory capabilities. - Pablo Pérez-Núñez; Paul Buitelaar; Jorge Díez 001; Oscar Luaces; Antonio Bahamonde (Appl. Soft Comput., 2025)