4 citations · 4 across the 5 of their papers we have counts for
5 papers
Hypergraph Normal World Models for Logical Visual Anomaly Detection
Weizhi Nie, Zibo Xu, Weijie Wang +1
Visual anomaly detection is often deployed with only normal training images. Most one-class detectors map test patches or features to a normal reference distribution. This works we…
Ask4VG: Risk-Aware Question Selection for Reducing Prior-Driven Answers in Medical VQA
Xiaorong Zhu, Qiang Li, Zibo Xu +2
Medical visual question answering requires models to ground their responses in image evidence, because visually unsupported answers can mislead downstream interpretation. However,…
Learning to Trim: End-to-End Causal Graph Pruning with Dynamic Anatomical Feature Banks for Medical VQA
Zibo Xu, Qiang Li, Weizhi Nie +1
Medical Visual Question Answering (MedVQA) models often exhibit limited generalization due to reliance on dataset-specific correlations, such as recurring anatomical patterns or qu…
Dual Causal Inference: Integrating Backdoor Adjustment and Instrumental Variable Learning for Medical VQA
Zibo Xu, Qiang Li, Ke Lu +3
Medical Visual Question Answering (MedVQA) aims to generate clinically reliable answers conditioned on complex medical images and questions. However, existing methods often overfit…
Structure Causal Models and LLMs Integration in Medical Visual Question Answering
Zibo Xu, Qiang Li, Weizhi Nie +2
Medical Visual Question Answering (MedVQA) aims to answer medical questions according to medical images. However, the complexity of medical data leads to confounders that are diffi…