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Xiaolu Kang

2 accepted papers

2026

Divide and Conquer: Reliable Multi-View Evidential Learning for Deepfake Detection

ICML 2026poster

With the evolution of generative models, deepfakes have achieved near-perfect semantic realism, leaving forensic traces only in subtle structural anomalies. However, existing single-view paradigms often fail to generalize, as dominant semantic features overwhelm subtle artifact cues within entangled…

Cited by 0SourceScholar
2025

Enhanced Contrastive Learning with Multi-view Longitudinal Data for Chest X-ray Report Generation

CVPR 2025poster

Automated radiology report generation offers an effective solution to alleviate radiologists' workload. However, most existing methods focus primarily on single or fixed-view images to model current disease conditions, which limits diagnostic accuracy and overlooks disease progression. Although some…