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LLM use challenges crowdsourced data integrity, survey finds

By PulseAugur Editorial · [2 sources] ·

A survey of 155 researchers reveals that the increasing use of LLMs poses a significant challenge to the integrity of crowdsourced data. While 44% of respondents have observed LLM usage in their data, many are unsure of effective mitigation strategies. Current detection methods, such as identifying stylistic patterns and rapid completion times, are considered insufficient by the research community. AI

IMPACT Highlights the growing difficulty in obtaining reliable human-generated data for AI training due to LLM proliferation.

RANK_REASON The cluster contains an academic paper detailing survey results on a specific research challenge.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

LLM use challenges crowdsourced data integrity, survey finds

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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Aswathy Velutharambath, Neele Falk, Sofie Labat, Tarun Tater, Amelie Wuehrl ·

    Can Crowdsourcing Survive the LLM Era? A Community Survey on Human Data Collection

    arXiv:2606.04924v1 Announce Type: new Abstract: The widespread use of Large Language Models (LLMs) as writing tools challenges the validity of crowdsourced data, as crowdworkers may outsource tasks to models. To better understand how this is addressed, we surveyed 155 researchers…

  2. arXiv cs.CL TIER_1 English(EN) · Amelie Wuehrl ·

    Can Crowdsourcing Survive the LLM Era? A Community Survey on Human Data Collection

    The widespread use of Large Language Models (LLMs) as writing tools challenges the validity of crowdsourced data, as crowdworkers may outsource tasks to models. To better understand how this is addressed, we surveyed 155 researchers in NLP and related disciplines about their expe…

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