{"ID":2896233,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.07919","arxiv_id":"2507.07919","title":"Plausible Counterfactual Explanations of Recommendations","abstract":"Explanations play a variety of roles in various recommender systems, from a legally mandated afterthought, through an integral element of user experience, to a key to persuasiveness. A natural and useful form of an explanation is the Counterfactual Explanation (CE). We present a method for generating highly plausible CEs in recommender systems and evaluate it both numerically and with a user study.","short_abstract":"Explanations play a variety of roles in various recommender systems, from a legally mandated afterthought, through an integral element of user experience, to a key to persuasiveness. A natural and useful form of an explanation is the Counterfactual Explanation (CE). We present a method for generating highly plausible C...","url_abs":"https://arxiv.org/abs/2507.07919","url_pdf":"https://arxiv.org/pdf/2507.07919v1","authors":"[\"Jakub Černý\",\"Jiří Němeček\",\"Ivan Dovica\",\"Jakub Mareček\"]","published":"2025-07-10T16:59:51Z","proceeding":"cs.LG","tasks":"[\"cs.LG\",\"cs.IR\"]","methods":"[]","has_code":false}