LLM-as-a-Judge: Toward World Models for Slate Recommendation Systems

• URL: http://arxiv.org/abs/2511.04541v1
• Date: Thu, 06 Nov 2025 16:54:54 GMT
• Title: LLM-as-a-Judge: Toward World Models for Slate Recommendation Systems
• Authors: Baptiste Bonin, Maxime Heuillet, Audrey Durand,
• Abstract summary: We investigate how Large Language Models (LLM) can act as world models of user preferences through pairwise reasoning over slates.<n>Our results reveal relationships between task performance and properties of the preference function captured by LLMs.
• Score: 5.310303349822993
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Modeling user preferences across domains remains a key challenge in slate recommendation (i.e. recommending an ordered sequence of items) research. We investigate how Large Language Models (LLM) can effectively act as world models of user preferences through pairwise reasoning over slates. We conduct an empirical study involving several LLMs on three tasks spanning different datasets. Our results reveal relationships between task performance and properties of the preference function captured by LLMs, hinting towards areas for improvement and highlighting the potential of LLMs as world models in recommender systems.

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