用大模型实时查证网页假新闻，还能解释依据并互动讨论。
Verify as You Go: An LLM-Powered Browser Extension for Fake News Detection
- 结合检索增强生成与大模型，动态验证网页内容真伪。
- 在250人用户研究中展现高可用性与查证可信度。
- 支持用户讨论和推送最新辟谣信息，提升参与感。
数字时代虚假新闻泛滥，严重威胁公众信任与民主制度，亟需高效、透明且以用户为中心的检测工具。现有浏览器插件普遍存在模型行为不透明、解释能力弱、用户参与度低等问题。本文提出 Aletheia，一款基于检索增强生成（RAG）与大语言模型（LLM）的新型浏览器扩展，可实时检测假新闻并提供基于证据的解释。系统还包含两个交互功能：讨论区（Discussion Hub）支持用户围绕被标记内容交流，以及‘保持知情’（Stay Informed）功能，自动推送近期权威辟谣信息。通过大量实验，我们证明 Aletheia 在检测性能上优于当前主流基线方法。此外，对250名参与者的用户研究进一步验证了系统的易用性与感知有效性，凸显其作为透明化反假新闻工具的潜力。
原文摘要 · Abstract (English)
The rampant spread of fake news in the digital age poses serious risks to public trust and democratic institutions, underscoring the need for effective, transparent, and user-centered detection tools. Existing browser extensions often fall short due to opaque model behavior, limited explanatory support, and a lack of meaningful user engagement. This paper introduces Aletheia, a novel browser extension that leverages Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) to detect fake news and provide evidence-based explanations. Aletheia further includes two interactive components: a Discussion Hub that enables user dialogue around flagged content and a Stay Informed feature that surfaces recent fact-checks. Through extensive experiments, we show that Aletheia outperforms state-of-the-art baselines in detection performance. Complementing this empirical evaluation, a complementary user study with 250 participants confirms the system's usability and perceived effectiveness, highlighting its potential as a transparent tool for combating online fake news.
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