4 citations · 6 across the 3 of their papers we have counts for
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cs.IR2026
The Utility of LLMs in Recommender Systems Explanation Evaluation
Kathrin Wardatzky, Oana Inel, Luca Rossetto +1
Explanations play a crucial role in creating trustworthy recommender systems (RS), yet choosing a good explanation method presents challenges. Many explanation methods exist, but l…
cs.IR2025★ 4 cited
D-RDW: Diversity-Driven Random Walks for News Recommender Systems
Runze Li, Lucien Heitz, Oana Inel +1
This paper introduces Diversity-Driven RandomWalks (D-RDW), a lightweight algorithm and re-ranking technique that generates diverse news recommendations. D-RDW is a societal recomm…
cs.IR2025★ 2 cited
Informfully Recommenders -- Reproducibility Framework for Diversity-aware Intra-session Recommendations
Lucien Heitz, Runze Li, Oana Inel +1
Norm-aware recommender systems have gained increased attention, especially for diversity optimization. The recommender systems community has well-established experimentation pipeli…