Li Auto（理想汽车）

Learning to Annotate Delayed and False AEB Events: A Practical System for Extreme Class Imbalance and Asymmetric Label Noise

学习标注延迟和误报AEB事件：针对极端类别不平衡和非对称标签噪声的实用系统

Mengxiang Hao, Xin Jiang, Xinghao Huang, Wenliang Su, Zhiteng Wang, Junjie Rao, Xiaotian Yang, Wei Liao, Chengyu Han, Gen Liang, Yulun Song, Zhitao Xu, Xianpeng Lang

机构 * Li Auto 纠错

AI总结 提出首个自动化AEB标注框架，通过特定数据增强和噪声抑制技术，解决极端类别不平衡和非对称标签噪声问题，将延迟/误报触发召回率提升80%，人工工作量减少50%。

Comments 8 pages, 5 figures, accepted by IEEE International Conference on Robotics and Automation (ICRA)

Journal ref 2026 IEEE International Conference on Robotics and Automation (ICRA)