3 papers
cs.CV2026
Visually-Guided Controllable Medical Image Generation via Fine-Grained Semantic Disentanglement
Xin Huang, Junjie Liang, Qingshan Hou +4
Medical image synthesis is crucial for alleviating data scarcity and privacy constraints. However, fine-tuning general text-to-image (T2I) models remains challenging, mainly due to…
cs.CL2026
Faithfulness Evaluation for Decoder-only LLM Attributions with Controlled Retained Information
Xin Huang, Antoni B. Chan
Large Language Models (LLMs) are increasingly evaluated with input attribution methods, yet comparing such explanations remains challenging. Existing soft-perturbation faithfulness…
cs.CV2024
Medical Image Debiasing by Learning Adaptive Agreement from a Biased Council
Luyang Luo, Xin Huang, Minghao Wang +2
Deep learning could be prone to learning shortcuts raised by dataset bias and result in inaccurate, unreliable, and unfair models, which impedes its adoption in real-world clinical…