6 citations · 6 across the 5 of their papers we have counts for
5 papers · 1 filter
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,…
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…
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…
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…