Consensus vs. Dissent: Dynamic LLM Modeling of Subjective Preferences in Group Recommenders

arXiv:2607.10235v1 Announce Type: new Abstract: Previous work in group recommender systems has demonstrated a sensitivity to the distribution of preferences within a group. Specifically, the selection of the preference aggregation strategy benefits from considering such group configurations. In this paper, we study whether LLMs are able to mimic this sensitivity and to select the ideal aggregation strategy (and corresponding recommendation) according to nuanced human perceptions of fairness, sat...