The proliferation of multimedia content on social media platforms has dramatically transformed how information is consumed and disseminated. While this shift enables real-time coverage of global events, it also facilitates the rapid spread of misinformation and disinformation, especially during crises such as wars, natural disasters, or elections. The rise of synthetic media and the reuse of authentic content in misleading contexts have intensified the need for robust multimedia verification tools. In this paper, we present a comprehensive system developed for the ACM Multimedia 2025 Grand Challenge on Multimedia Verification. Our system assesses the authenticity and contextual accuracy of multimedia content in multilingual settings and generates both expert-oriented verification reports and accessible summaries for the general public. We introduce a unified verification pipeline that integrates visual forensics, textual analysis, and multimodal reasoning, and propose a hybrid approach to detect out-of-context (OOC) media through semantic similarity, temporal alignment, and geolocation cues. Extensive evaluations on the Grand Challenge benchmark demonstrate the system's effectiveness across diverse real-world scenarios. Our contributions advance the state of the art in multimedia verification and offer practical tools for journalists, fact-checkers, and researchers confronting information integrity challenges in the digital age.

翻译：社交媒体平台上多媒体内容的激增极大地改变了信息的消费与传播方式。这一转变虽然实现了全球事件的实时报道，但也助长了错误信息和虚假信息的快速传播，尤其是在战争、自然灾害或选举等危机期间。合成媒体的兴起以及真实内容在误导性语境中的再利用，加强了对鲁棒多媒体验证工具的迫切需求。本文介绍了为ACM Multimedia 2025多媒体验证大挑战赛开发的一套综合性系统。该系统评估多语言环境下多媒体内容的真实性与上下文准确性，并生成面向专家的验证报告以及面向公众的易懂摘要。我们提出了一种统一的验证流程，该流程整合了视觉取证、文本分析与多模态推理，并通过语义相似性、时间对齐和地理位置线索，提出了一种检测上下文不符媒体的混合方法。在大挑战赛基准上的广泛评估证明了该系统在多样化现实场景中的有效性。我们的贡献推动了多媒体验证技术的进步，并为记者、事实核查人员和研究人员应对数字时代信息完整性挑战提供了实用工具。