VLSP 2025 MLQA-TSR Challenge: Vietnamese Multimodal Legal Question Answering on Traffic Sign Regulation
Luu, Son T., Vo, Trung, Nguyen, Hiep, Tran, Khanh Quoc, Van Nguyen, Kiet, Tran, Vu, Nguyen, Ngan Luu-Thuy, Nguyen, Le-Minh
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Oct-24-2025
- Country:
- Asia
- Cambodia > Tboung Khmum Province
- Suong (0.04)
- Japan (0.04)
- Thailand > Bangkok
- Bangkok (0.04)
- Vietnam > Hồ Chí Minh City
- Hồ Chí Minh City (0.04)
- Cambodia > Tboung Khmum Province
- Europe > Italy
- Calabria > Catanzaro Province > Catanzaro (0.04)
- Asia
- Genre:
- Research Report (0.50)
- Industry:
- Law (1.00)
- Technology: