自动识别多语言短视频中的可信核查内容，辅助人工核验。
ShortCheck: Checkworthiness Detection of Multilingual Short-Form Videos
- 模块化流水线整合语音转写、文字识别、深度伪造检测等技术。
- 在双语数据集上加权F1超70%，具备实用核查能力。
- 适合媒体机构和事实核查团队快速筛选高风险视频。
TikTok等短视频平台因多模态、动态性和噪声内容，给虚假信息检测带来独特挑战。我们提出ShortCheck，一个模块化、仅推理的自动化系统，通过友好的用户界面帮助人工核查者识别值得核查的短视频。该系统集成语音转写、OCR、物体与深度伪造检测、视频转文本摘要及声明验证功能。ShortCheck在两个手动标注的多语言TikTok视频数据集上进行验证，加权F1得分超过70%，表现出良好性能。
原文摘要 · Abstract (English)
Short-form video platforms like TikTok present unique challenges for misinformation detection due to their multimodal, dynamic, and noisy content. We present ShortCheck, a modular, inference-only pipeline with a user-friendly interface that automatically identifies checkworthy short-form videos to help human fact-checkers. The system integrates speech transcription, OCR, object and deepfake detection, video-to-text summarization, and claim verification. ShortCheck is validated by evaluating it on two manually annotated datasets with TikTok videos in a multilingual setting. The pipeline achieves promising results with F1-weighted score over 70\%.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。