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REALM: A Dataset of Real-World LLM Use Cases

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arxiv 2503.18792 v2 pith:AUQHLRP2 submitted 2025-03-24 cs.HC cs.AIcs.CLcs.CY

classification cs.HCcs.AIcs.CLcs.CY
keywords applicationsrealmreal-worldcasesdatasetllmssocietalusers
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Large Language Models (LLMs), such as the GPT series, have driven significant industrial applications, leading to economic and societal transformations. However, a comprehensive understanding of their real-world applications remains limited. To address this, we introduce REALM, a dataset of over 94,000 LLM use cases collected from Reddit and news articles. REALM captures two key dimensions: the diverse applications of LLMs and the demographics of their users. It categorizes LLM applications and explores how users' occupations relate to the types of applications they use. By integrating real-world data, REALM offers insights into LLM adoption across different domains, providing a foundation for future research on their evolving societal roles.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A Personalized Conversational Benchmark: Towards Simulating Personalized Conversations

    cs.CL 2025-05 conditional novelty 6.0 of 10

    PERSONACONVBENCH is a new Reddit-based benchmark showing that LLMs predict sentiment, community scores, and next replies better when given a user's multi-turn conversation history, and it releases public data and code.

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