3 papers
cs.AI2026
REAL: Resolving Knowledge Conflicts in Knowledge-Intensive Visual Question Answering via Reasoning-Pivot Alignment
Kai Ye, Xianwei Mao, Sheng Zhou +6
Knowledge-intensive Visual Question Answering (KI-VQA) frequently suffers from severe knowledge conflicts caused by the inherent limitations of open-domain retrieval. However, exis…
cs.AI2026
Doc-CoB: Enhancing Document Understanding with Visual Chain-of-Boxes Reasoning
Ye Mo, Kai Ye, Xianwei Mao +9
Document understanding aims to perform question answering and information extraction over document images, where the visual content is highly information-dense and most queries rel…
cs.CV2026
MaS-VQA: A Mask-and-Select Framework for Knowledge-Based Visual Question Answering
Xianwei Mao, Kai Ye, Sheng Zhou +4
Knowledge-based Visual Question Answering (KB-VQA) requires models to answer questions by integrating visual information with external knowledge. However, retrieved knowledge is of…