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cs.IR2026
Spectral Biclustering-Driven Scalability for Post-Hoc Explainability in Recommender Systems
Jose L. Salmeron, Irina Arévalo
Explainability in recommender systems is essential for ensuring transparency, accountability, and trust, yet existing post-hoc methods often encounter severe scalability challenges…
cs.IR2025
Model-agnostic post-hoc explainability for recommender systems
Irina Arévalo, Jose L Salmeron
Recommender systems often benefit from complex feature embeddings and deep learning algorithms, which deliver sophisticated recommendations that enhance user experience, engagement…