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RecRec: Algorithmic Recourse for Recommender Systems https://arxiv.org/pdf/2308.14916.pdf #preprint ML models underlying #RecSys are often opaque, making it difficult for users, content providers, and developers to understand why certain recommendations are made.

To address this problem, this paper proposes a recourse framework for recommender systems. A recourse is a set of actions that, if executed, would modify the recommendations (or ranking) of an item in the desired manner.