实时检测直播视频中的虚假信息，填补了在线动态监测的空白。
Online Misinformation Detection in Live Streaming Videos
- 提出在线直播虚假信息检测新任务（MDLS），突破传统离线分析局限。
- 构建面向实时场景的检测框架，支持流式数据持续分析与响应。
- 为AI竞赛和实际应用提供可落地的解决方案，适合安全与内容审核团队参考。
在线虚假信息检测是一项重要议题，已有方法用于识别和遏制各类形式的虚假信息。然而，以往研究多基于离线处理模式。本文提出一个尚未被充分探索的现实检测场景：直播视频中的在线虚假信息检测（MDLS）。我们系统地定义了该任务，阐明其重要性与挑战。同时，提出了将该问题转化为人工智能挑战的可行路径，并探讨潜在解决方案，为未来研究与实际应用提供方向。
原文摘要 · Abstract (English)
Online misinformation detection is an important issue and methods are proposed to detect and curb misinformation in various forms. However, previous studies are conducted in an offline manner. We claim a realistic misinformation detection setting that has not been studied yet is online misinformation detection in live streaming videos (MDLS). In the proposal, we formulate the problem of MDLS and illustrate the importance and the challenge of the task. Besides, we propose feasible ways of developing the problem into AI challenges as well as potential solutions to the problem.
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