Can We Build Recommender Systems That Are More Robust, Trustworthy And Well-Rounded?
The ubiquity of personalized recommendations has led to a surge of interest in recommender systems research; however, evaluating model performance across use cases is still difficult.
Building on the success of EvalRS 2022 and Reclist, we are back with a broader scope and a new interactive format: our workshop focuses on multi-faceted evaluation for recommender systems, mixing a traditional research track (with prizes for innovative papers) and a hackathon , to live and breath the challenges with working code (with prizes for the best projects).
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