2 papers
cs.IR2025
FIRE: Faithful Interpretable Recommendation Explanations
S. M. F. Sani, Asal Meskin, Mohammad Amanlou +1
Natural language explanations in recommender systems are often framed as a review generation task, leveraging user reviews as ground-truth supervision. While convenient, this appro…
cs.LG2023
Epsilon non-Greedy: A Bandit Approach for Unbiased Recommendation via Uniform Data
S. M. F. Sani, Seyed Abbas Hosseini, Hamid R. Rabiee
Often, recommendation systems employ continuous training, leading to a self-feedback loop bias in which the system becomes biased toward its previous recommendations. Recent studie…