Latest research in Evidence Triaging for Mobile Forensics focuses on developing AI-driven methodologies, machine learning models, and practical tools to efficiently prioritize, extract, and analyze digital evidence from mobile devices. Studies emphasize the use of metadata analysis, file classification, and on-site triage applications to accelerate investigations while handling large volumes of data. Research also explores multidisciplinary approaches integrating eXplainable AI, IoT, blockchain, and emerging technologies to improve decision-making in evidence prioritization. These advancements collectively aim to enhance the accuracy, efficiency, and reliability of mobile forensic investigations, enabling investigators to focus on high-value evidence and optimize forensic workflows.