Exploring the Potential of LLMs as Personalized Assistants: Dataset, Evaluation, and Analysis

• URL: http://arxiv.org/abs/2506.01262v1
• Date: Mon, 02 Jun 2025 02:25:46 GMT
• Title: Exploring the Potential of LLMs as Personalized Assistants: Dataset, Evaluation, and Analysis
• Authors: Jisoo Mok, Ik-hwan Kim, Sangkwon Park, Sungroh Yoon,
• Abstract summary: HiCUPID is a new benchmark to probe and unleash the potential of Large Language Models (LLMs) to deliver personalized responses.<n>Alongside a conversational dataset, HiCUPID provides a Llama-3.2-based automated evaluation model.
• Score: 35.18369708380039
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Personalized AI assistants, a hallmark of the human-like capabilities of Large Language Models (LLMs), are a challenging application that intertwines multiple problems in LLM research. Despite the growing interest in the development of personalized assistants, the lack of an open-source conversational dataset tailored for personalization remains a significant obstacle for researchers in the field. To address this research gap, we introduce HiCUPID, a new benchmark to probe and unleash the potential of LLMs to deliver personalized responses. Alongside a conversational dataset, HiCUPID provides a Llama-3.2-based automated evaluation model whose assessment closely mirrors human preferences. We release our dataset, evaluation model, and code at https://github.com/12kimih/HiCUPID.

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