VLSP 2025 MLQA-TSR Challenge: Vietnamese Multimodal Legal Question Answering on Traffic Sign Regulation
October 23, 2025 ยท Declared Dead ยท ๐ arXiv.org
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Authors
Son T. Luu, Trung Vo, Hiep Nguyen, Khanh Quoc Tran, Kiet Van Nguyen, Vu Tran, Ngan Luu-Thuy Nguyen, Le-Minh Nguyen
arXiv ID
2510.20381
Category
cs.CL: Computation & Language
Cross-listed
cs.AI
Citations
0
Venue
arXiv.org
Last Checked
6 months ago
Abstract
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.
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