Xianglong Du — accepted AI-conference papers

2026

Towards Stealthy and Effective Backdoor Attacks on Lane Detection: A Naturalistic Data Poisoning Approach

Yifan Liao, Yuxin Cao, Yedi Zhang, Wentao He, Yan Xiao, Xianglong Du +2

CVPR 2026

Deep learning-based lane detection (LD) plays a critical role in autonomous driving and advanced driver assistance systems. However, its vulnerability to backdoor attacks presents a significant security concern. Existing backdoor attack methods on LD often exhibit limited practical utility due to th

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2026

When Sample Selection Bias Precipitates Model Collapse

Xinbao Qiao, Xianglong Du, Wei Liu, Jingqi Zhang, Peihua Mai, Meng Zhang +1

ICML 2026poster

The proliferation of recursive synthetic data training promises to alleviate data scarcity but introduces the existential risk of model collapse, wherein recursive training on synthetic data erodes distributional tails and homogenizes outputs. Current literature identifies data selection as a pivota…

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