English(EN)Not All That Is Fluent Is Factual: Investigating Hallucinations of Large Language Models in Academic Writing
研究表明，大型语言模型在学术和医疗领域会出现幻觉
作者PulseAugur 编辑部·[16 个来源]·
一项新近发布在arXiv上的研究调查了四种流行的大型语言模型——ChatGPT、Grok、Gemini和Copilot——在用于学术写作时产生幻觉的倾向。该研究引入了一个“幻觉指数”（HI），发现Grok和Copilot在引用生成方面表现更好，但在抽象提示方面遇到困难，而Gemini和ChatGPT则表现出更好的语气控制，但事实幻觉的风险更高。研究得出结论，幻觉行为受任务类型和提示条件的影响，而非仅仅由模型架构决定。另外，Gary Marcus强调了多项研究表明，当前的大型语言模型在医疗建议方面并不可靠，常常自信地提供不准确或虚假的信息，不应将其用于无监督的临床决策。
AI
The growing accessibility of Large Language Models via conversational interfaces capable of responding to users' questions by drawing on, synthesizing, and citing information from the web (i.e., Generative Search Engines) has simplified the information-seeking process for users. …
arXiv cs.CL
TIER_1English(EN)·Humam Khan, Md Tabrez Nafis, Shahab Saquib Sohail, Aqeel Khalique, Rehan Hasan Khan·
arXiv:2605.04171v1 Announce Type: new Abstract: Large Language models (LLMs) show extraordinary abilities, but they are still prone to hallucinations, especially when we use them for generating Academic content. We have investigated four popular LLMs, ChatGPT, Grok, Gemini, and C…
Large Language models (LLMs) show extraordinary abilities, but they are still prone to hallucinations, especially when we use them for generating Academic content. We have investigated four popular LLMs, ChatGPT, Grok, Gemini, and Copilot for hallucinations specifically for acade…
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