ReMMD: Realistic Multilingual Multi-Image Agentic Verification for Multimodal Misinformation Detection

ReMMD introduces a framework for multimodal misinformation detection that addresses the limitations of existing benchmarks by incorporating realistic scenarios with multilingual narratives and multiple images. The framework includes ReMMDBench, a benchmark with 500 samples and various veracity and distortion labels, and ReMMD-Agent, which utilizes persistent memory to improve evidence verification and achieve a five-way veracity accuracy of 41.80% using GPT-5.2, while significantly reducing operational costs compared to previous agents. This advancement is crucial for practitioners as it enhances the detection of complex misinformation across diverse formats and languages.