2025/10/23 by Son T. Luu, Luu, Son T., Trung Quang Vo +13
Computer Science · #Topic Modeling #Natural Language Processing Techniques #Multimodal Machine Learning Applications
paper · pdf · doi:10.48550/arxiv.2510.20381
This paper presents the VLSP 2025 MLQA-TSR - the multimodal legal question answering on traffic sign regulation shared task at VLSP 2025. VLSP 2025 MLQA-TSR comprises two subtasks: multimodal legal retrieval and multimodal question answering. The goal is to advance research on Vietnamese multimodal legal text processing and to provide a benchmark dataset for building and evaluating intelligent systems in multimodal legal domains, with a focus on traffic sign regulation in Vietnam. The best-reported results on VLSP 2025 MLQA-TSR are an F2 score of 64.55% for multimodal legal retrieval and an accuracy of 86.30% for multimodal question answering.