English(EN) Can Crowdsourcing Survive the LLM Era? A Community Survey on Human Data Collection

调查发现大型语言模型的使用挑战众包数据完整性

作者 PulseAugur 编辑部 · [2 个来源] · 2026-06-03 14:18

一项针对155名研究人员的调查显示，大型语言模型（LLM）的日益普及对众包数据的完整性构成了重大挑战。尽管44%的受访者观察到他们的数据中存在LLM的使用，但许多人仍不确定有效的缓解策略。研究界认为，目前的检测方法，如识别风格模式和快速完成时间，尚不足以应对这一挑战。 AI

影响凸显了由于大型语言模型的泛滥，为AI训练获取可靠的人类生成数据日益困难。

排序理由该集群包含一篇详细介绍特定研究挑战的调查结果的学术论文。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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Newsworthiness bucket: Research; 该集群包含一篇详细介绍特定研究挑战的调查结果的学术论文。
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arXiv cs.CL TIER_1 English(EN) · Aswathy Velutharambath, Neele Falk, Sofie Labat, Tarun Tater, Amelie Wuehrl · 2026-06-04 04:00

众包能否在大型语言模型时代生存？一项关于人类数据收集的社区调查

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…
arXiv cs.CL TIER_1 English(EN) · Amelie Wuehrl · 2026-06-03 14:18

众包能否在大型语言模型时代生存？一项关于人类数据收集的社区调查

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…