23 citations · 37 across the 5 of their papers we have counts for
5 papers
Normative Alignment of Recommender Systems via Internal Label Shift
Johannes Kruse, Kasper Lindskow, Michael Riis Andersen +4
We introduce NAILS (Normative Alignment of Recommender Systems via Internal Label Shift), a simple and scalable method for aligning recommendation outputs with target distributions…
ZoRRO: A Zero-Weight Personalized Recommender System for Scalable News Recommendation
Johannes Kruse, Ryotaro Shimizu, Kasper Lindskow +4
We present ZoRRO (Zero-Weight Personalized Recommender System), a zero-weight, training-free framework for personalized news recommendation designed for scalable real-world deploym…
EB-NeRD: A Large-Scale Dataset for News Recommendation
Johannes Kruse, Kasper Lindskow, Saikishore Kalloori +6
Personalized content recommendations have been pivotal to the content experience in digital media from video streaming to social networks. However, several domain specific challeng…
Disentangling Likes and Dislikes in Personalized Generative Explainable Recommendation
Ryotaro Shimizu, Takashi Wada, Yu Wang +9
Recent research on explainable recommendation generally frames the task as a standard text generation problem, and evaluates models simply based on the textual similarity between t…
RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations
Johannes Kruse, Kasper Lindskow, Saikishore Kalloori +6
The RecSys Challenge 2024 aims to advance news recommendation by addressing both the technical and normative challenges inherent in designing effective and responsible recommender…