Superpixel-Guided Iterative Learning from Noisy Labels for Medical Image Segmentation. - Shuailin Li; Zhitong Gao; Xuming He 001 (MICCAI (1), 2021)

Modeling Multimodal Aleatoric Uncertainty in Segmentation with Mixture of Stochastic Expert. - Zhitong Gao; Yucong Chen; Chuyu Zhang; Xuming He 001 (CoRR, 2022)

The Robust Semantic Segmentation UNCV2023 Challenge Results. - Xuanlong Yu; Yi Zuo; Zitao Wang; Xiaowen Zhang; Jiaxuan Zhao; Yuting Yang 008; Licheng Jiao; Rui Peng; Xinyi Wang; Junpei Zhang; Kexin Zhang 003; Fang Liu 001; et al. (ICCV (Workshops), 2023)

Modeling Multimodal Aleatoric Uncertainty in Segmentation with Mixture of Stochastic Experts. - Zhitong Gao; Yucong Chen; Chuyu Zhang; Xuming He 001 (ICLR, 2023)

MILD: Modeling the Instance Learning Dynamics for Learning with Noisy Labels. - Chuanyang Hu; Shipeng Yan; Zhitong Gao; Xuming He 001 (IJCAI, 2023)

Gradient-Map-Guided Adaptive Domain Generalization for Cross Modality MRI Segmentation. - Bingnan Li; Zhitong Gao; Xuming He 001 (ML4H@NeurIPS, 2023)

ATTA: Anomaly-aware Test-Time Adaptation for Out-of-Distribution Detection in Segmentation. - Zhitong Gao; Shipeng Yan; Xuming He 001 (NeurIPS, 2023)

Generalize or Detect? Towards Robust Semantic Segmentation Under Multiple Distribution Shifts. - Zhitong Gao; Bingnan Li; Mathieu Salzmann; Xuming He 001 (NeurIPS, 2024)

Large (Vision) Language Models are Unsupervised In-Context Learners. - Artyom Gadetsky; Andrei Atanov; Yulun Jiang; Zhitong Gao; Ghazal Hosseini Mighan; Amir Zamir; Maria Brbic (ICLR, 2025)