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Nava Tintarev

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#large language models Open access Sep 2026

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

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...

Cedric Waterschoot, Nava Tintarev, Francesco Barile · 0 citations
#large language models Sep 2026

Consistent Explainers or Unreliable Narrators: Systematic Differences in Consistency and Sensitivity Across Large Language Models for Group Recommendations

Group Recommender Systems (GRS) face the challenge of combining conflicting individual preferences. While Large Language Models (LLMs) are increasingly integrated into GRS, they may introduce risks regarding output inconsistency or sensitivity to group characteristics. In this paper, we analyze LLMs acting as both deci...

Cedric Waterschoot, Nava Tintarev, Francesco Barile · 0 citations

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