1 code implementation • 1 Jun 2023 • Guangyuan Jiang, Manjie Xu, Shiji Xin, Wei Liang, Yujia Peng, Chi Zhang, Yixin Zhu
To fill in this gap, we introduce the MachinE Word Learning (MEWL) benchmark to assess how machines learn word meaning in grounded visual scenes.
no code implementations • 18 Dec 2022 • Shiji Xin, Yifei Wang, Jingtong Su, Yisen Wang
Extensive experiments show that our proposed DAT can effectively remove domain-varying features and improve OOD generalization under both correlation shift and diversity shift.
no code implementations • 29 Sep 2021 • Shiji Xin, Yifei Wang, Jingtong Su, Yisen Wang
Extensive experiments show that our proposed DAT can effectively remove the domain-varying features and improve OOD generalization on both correlation shift and diversity shift tasks.
2 code implementations • 1 Jul 2021 • Binghui Li, Shiji Xin, Qizhe Zhang
Moreover, we give the theoretical analysis of the ensemble method based on the $1$-Lipschitz property on the certified robustness, which ensures the effectiveness and stability of the algorithm.