Author

Kathrin Wardatzky

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Review Open access Sep 2026

The Impact of Explanation Characteristics on the Effects of Recommender Systems Explanations

There seems to be a consensus that adding explanations to AI systems, such as recommender systems, can have positive effects, such as increasing a user’s trust, the transparency of the system, or the efficiency of a decision-making process. It is to this date unclear, though, how an explanation needs to be designed to...

Kathrin Wardatzky, Oana Inel, Luca Rossetto et al. · ACM Computing Surveys · 0 citations

#artificial intelligence Book Open access Aug 2026

The Utility of LLMs in Recommender Systems Explanation Evaluation

The utility of LLMs in selecting an effective explanation method for a given application is studied and four practical recommendations are derived: keep explanation-generation prompts concise, prefer larger models for evaluation, pre-test evaluation constructs, and audit explanations for factual accuracy.

Kathrin Wardatzky, Oana Inel, Luca Rossetto et al. · Proceedings of the 20th ACM... · 0 citations