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Although explainability is critical for trustworthy AI, Group Recommender Systems (GRS) lack dedicated, flexible software tools. To address this, we present GREX, a novel, open-source Python library designed to facilitate the development and evaluation of explanations in group settings. GREX is built on a modular and extensible architecture, providing implementations of three distinct explanation paradigms: counterfactual (Sliding-Window-Weighted), rule-based (EXPGRS), and local model-agnostic (LORE4GROUPS). We conducted a comprehensive description of GREX stages, overall including data preparation, training, recommendation, and explanation. GREX is focused on empowering researchers and practitioners to systematically develop and compare Explainable AI (XAI) methods, fostering progress in transparent and user-centric GRS.

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GREX: A Platform for Supporting Explanations in Group Recommender Systems

  • 会议论文

  • 发表日期：

    2026年

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  • Mateus Toledo,
  • Raciel Yera,
  • Manuel J. Barranco,
  • Bapi Dutta

摘要

Although explainability is critical for trustworthy AI, Group Recommender Systems (GRS) lack dedicated, flexible software tools. To address this, we present GREX, a novel, open-source Python library designed to facilitate the development and evaluation of explanations in group settings. GREX is built on a modular and extensible architecture, providing implementations of three distinct explanation paradigms: counterfactual (Sliding-Window-Weighted), rule-based (EXPGRS), and local model-agnostic (LORE4GROUPS). We conducted a comprehensive description of GREX stages, overall including data preparation, training, recommendation, and explanation. GREX is focused on empowering researchers and practitioners to systematically develop and compare Explainable AI (XAI) methods, fostering progress in transparent and user-centric GRS.