1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.IR2026
The Bandit's Blind Spot: The Critical Role of User State Representation in Recommender Systems
Pedro R. Pires, Gregorio F. Azevedo, Rafael T. Sereicikas +2
With the increasing availability of online information, recommender systems have become an important tool for many web-based systems. Due to the continuous aspect of recommendation…
cs.LG2026★ 1 cited
Exploitation Over Exploration: Unmasking the Bias in Linear Bandit Recommender Offline Evaluation
Pedro R. Pires, Gregorio F. Azevedo, Pietro L. Campos +2
Multi-Armed Bandit (MAB) algorithms are widely used in recommender systems that require continuous, incremental learning. A core aspect of MABs is the exploration-exploitation trad…