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VLSP 2025 MLQA-TSR Challenge: Vietnamese Multimodal Legal Question Answering on Traffic Sign Regulation

arXiv 2510.20381 ↗First posted 23 Oct 2025cs.CL cs.AIcited by 0

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Abstract (arXiv)

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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References · 8

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
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  7. 2024What is YOLOv8: An In-Depth Exploration of the Internal Features of the Next-Generation Object Detectorcited by 45
  8. 2024VLSP 2023 -- LTER: A Summary of the Challenge on Legal Textual Entailment Recognitioncited by 1

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