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.

翻译：本文介绍了VLSP 2025 MLQA-TSR——即VLSP 2025会议中关于交通标志法规的多模态法律问答共享任务。VLSP 2025 MLQA-TSR包含两个子任务：多模态法律检索与多模态问答。其目标是推动越南语多模态法律文本处理的研究，并为构建和评估多模态法律领域的智能系统提供一个基准数据集，重点关注越南的交通标志法规。在VLSP 2025 MLQA-TSR上报告的最佳结果为：多模态法律检索的F2分数达到64.55%，多模态问答的准确率达到86.30%。