4 papers
DocOCR-Eval: A Correction-Based Framework for OCR Tool Selection Without Ground Truth
Zihan Xu, Puzhen Wu, Lawrence Chun Man Lau +4
Document parsing is a foundational step for document understanding tasks such as visual question answering and key information extraction, as it transforms unstructured scanned ima…
Docs2Synth: A Synthetic Data Trained Retriever Framework for Scanned Visually Rich Documents Understanding
Yihao Ding, Qiang Sun, Puzhen Wu +3
Document understanding (VRDU) in regulated domains is particularly challenging, since scanned documents often contain sensitive, evolving, and domain specific knowledge. This leads…
A Disease-Aware Dual-Stage Framework for Chest X-ray Report Generation
Puzhen Wu, Hexin Dong, Yi Lin +2
Radiology report generation from chest X-rays is an important task in artificial intelligence with the potential to greatly reduce radiologists' workload and shorten patient wait t…
AMD-Mamba: A Phenotype-Aware Multi-Modal Framework for Robust AMD Prognosis
Puzhen Wu, Mingquan Lin, Qingyu Chen +4
Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss, making effective prognosis crucial for timely intervention. In this work, we propose AMD-Mamb…