Zhou, Xiong

17 publications

ICCV 2025 Joint Asymmetric Loss for Learning with Noisy Labels Jialiang Wang, Xianming Liu, Xiong Zhou, Gangfeng Hu, Deming Zhai, Junjun Jiang, Xiangyang Ji

ICML 2025 Proposer-Agent-Evaluator (PAE): Autonomous Skill Discovery for Foundation Model Internet Agents Yifei Zhou, Qianlan Yang, Kaixiang Lin, Min Bai, Xiong Zhou, Yu-Xiong Wang, Sergey Levine, Li Erran Li

ICCV 2025 Robust Test-Time Adaptation for Single Image Denoising Using Deep Gaussian Prior Qing Ma, Pengwei Liang, Xiong Zhou, Jiayi Ma, Junjun Jiang, Zhe Peng

NeurIPS 2024 $\epsilon$-SoftMax: Approximating One-Hot Vectors for Mitigating Label Noise Jialiang Wang, Xiong Zhou, Deming Zhai, Junjun Jiang, Xiangyang Ji, Xianming Liu

CVPRW 2024 AffordanceLLM: Grounding Affordance from Vision Language Models Shengyi Qian, Weifeng Chen, Min Bai, Xiong Zhou, Zhuowen Tu, Li Erran Li

ICLR 2024 Neural Field Classifiers via Target Encoding and Classification Loss Xindi Yang, Zeke Xie, Xiong Zhou, Boyu Liu, Buhua Liu, Yi Liu, Haoran Wang, Yunfeng Cai, Mingming Sun

ICLR 2024 Variance-Enlarged Poisson Learning for Graph-Based Semi-Supervised Learning with Extremely Sparse Labeled Data Xiong Zhou, Xianming Liu, Hao Yu, Jialiang Wang, Zeke Xie, Junjun Jiang, Xiangyang Ji

ECCV 2024 ViGoR: Improving Visual Grounding of Large Vision Language Models with Fine-Grained Reward Modeling Siming Yan, Min Bai, Weifeng Chen, Xiong Zhou, Qixing Huang, Li Erran Li

ICLR 2024 Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs Xiong Zhou, Xianming Liu, Feilong Zhang, Gang Wu, Deming Zhai, Junjun Jiang, Xiangyang Ji

NeurIPSW 2023 Multi-Head CLIP: Improving CLIP with Diverse Representations and Flat Minima Mo Zhou, Xiong Zhou, Li Erran Li, Stefano Ermon, Rong Ge

ICML 2023 No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server Computation Feilong Zhang, Xianming Liu, Shiyi Lin, Gang Wu, Xiong Zhou, Junjun Jiang, Xiangyang Ji

JMLR 2023 On the Dynamics Under the Unhinged Loss and Beyond Xiong Zhou, Xianming Liu, Hanzhang Wang, Deming Zhai, Junjun Jiang, Xiangyang Ji

AAAI 2022 Exploiting Invariance in Training Deep Neural Networks Chengxi Ye, Xiong Zhou, Tristan McKinney, Yanfeng Liu, Qinggang Zhou, Fedor Zhdanov

ICLR 2022 Learning Towards the Largest Margins Xiong Zhou, Xianming Liu, Deming Zhai, Junjun Jiang, Xin Gao, Xiangyang Ji

ICML 2022 Prototype-Anchored Learning for Learning with Imperfect Annotations Xiong Zhou, Xianming Liu, Deming Zhai, Junjun Jiang, Xin Gao, Xiangyang Ji

ICML 2021 Asymmetric Loss Functions for Learning with Noisy Labels Xiong Zhou, Xianming Liu, Junjun Jiang, Xin Gao, Xiangyang Ji

ICCV 2021 Learning with Noisy Labels via Sparse Regularization Xiong Zhou, Xianming Liu, Chenyang Wang, Deming Zhai, Junjun Jiang, Xiangyang Ji