Exploring the Zero-Shot Known-Item Retrieval Capabilities of LLMs for Casual Leisure Information Needs

The rapidly increasing popularity of LLM-powered chatbots has led to them being used for a increasing number of different tasks by the general public.One of these tasks is searching for information instead of using a search engine.Previous work has shown that complex search tasks can be problematic for traditional search engines to solve, but little is known about the capability of LLMs on the same task.We compared four LLMs on their capability to answer a specific type of complex search task: known-item requests from casual leisure domains.We constructed a test collection by gathering known-item requests for books, games and movies from online forums along with verified answers by the original requester.We prompted four LLMs multiple times with the same prompt and analyzed the results with respect to accuracy and the degree to which answers were fabricated by the LLM.Our results show that LLMs are not particularly effective in fulfilling these complex casual leisure needs, but there are are big differences between LLMs and across domains. CCS Concepts

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Publication Details

Published
2025-03-24
DOI
https://doi.org/10.1145/3698204.3716466
Citations
2
Primary Topic
Technology and Data Analysis
Type
article
Field-Weighted Citation Impact
6.49

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article

Exploring the Zero-Shot Known-Item Retrieval Capabilities of LLMs for Casual Leisure Information Needs

Toine Bogers, Mette Skov, Vivien Petras, Mark Hall et al.
2 citations
Technology and Data Analysis
6.49
article

Exploring the Zero-Shot Known-Item Retrieval Capabilities of LLMs for Casual Leisure Information Needs

Toine Bogers, Mette Skov, Vivien Petras, Mark Hall, Marijn Koolen, Maria Gäde
article en
2 citations

Abstract

The rapidly increasing popularity of LLM-powered chatbots has led to them being used for a increasing number of different tasks by the general public.One of these tasks is searching for information instead of using a search engine.Previous work has shown that complex search tasks can be problematic for traditional search engines to solve, but little is known about the capability of LLMs on the same task.We compared four LLMs on their capability to answer a specific type of complex search task: known-item requests from casual leisure domains.We constructed a test collection by gathering known-item requests for books, games and movies from online forums along with verified answers by the original requester.We prompted four LLMs multiple times with the same prompt and analyzed the results with respect to accuracy and the degree to which answers were fabricated by the LLM.Our results show that LLMs are not particularly effective in fulfilling these complex casual leisure needs, but there are are big differences between LLMs and across domains. CCS Concepts

Royal Netherlands Academy of Arts and Sciences (NL), The Open University (GB), Humboldt-Universität zu Berlin (DE), IT University of Copenhagen (DK), Aalborg University (DK)
Danmarks Grundforskningsfond
Openalex Percentile: Top 4%
Technology and Data Analysis
6.49
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Exploring the Zero-Shot Known-Item Retrieval Capabilities of LLMs for Casual Leisure Information Needs — Toine Bogers, Mette Skov, et al. · (2025) | TGRS Research Map | TGRS