Phuc-Lu Le
2026
SemViQA: A Semantic Question Answering System for Vietnamese Information Fact-Checking
Dien X. Tran | Nam V. Nguyen | Tran Tan Thanh | Anh T. Hoang | Duong Văn Tài | Lê Thanh Di | Phuc-Lu Le
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026)
Dien X. Tran | Nam V. Nguyen | Tran Tan Thanh | Anh T. Hoang | Duong Văn Tài | Lê Thanh Di | Phuc-Lu Le
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026)
Recent advances in LLMs have accelerated both information generation and misinformation, especially in low-resource languages like Vietnamese, motivating robust fact-checking systems. Existing methods struggle with semantic ambiguity, homonyms, and complex linguistic structures, often trading accuracy for efficiency. We introduce SemViQA, a novel Vietnamese fact-checking framework integrating Semantic-based Evidence Retrieval (SER) and Two-step Verdict Classification (TVC). Our approach balances precision and speed, achieving state-of-the-art results with 78.97% strict accuracy on ISE-DSC01 and 80.82% on ViWikiFC, securing 1st place in the UIT Data Science Challenge. Additionally, SemViQA Faster improves inference speed 7× while maintaining competitive accuracy. SemViQA sets a new benchmark for Vietnamese fact verification, advancing the fight against misinformation.