Xiaobo Xia

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 61

Top Topics

Diffusion Models

Image Completion

Top Venues

Publications

Lei Zhang, Yunshui Li, Jiaming Li, Xiaobo Xia, Jiaxi Yang, Run Luo, Minzheng Wang, Longze Chen, Junhao Liu, Min Yang
Hierarchical Context Pruning: Optimizing Real-World Code Completion with Repository-Level Pretrained Code LLMs. CoRR (2024)
Yunshui Li, Binyuan Hui, Xiaobo Xia, Jiaxi Yang, Min Yang, Lei Zhang, Shuzheng Si, Ling-Hao Chen, Junhao Liu, Tongliang Liu, Fei Huang, Yongbin Li
One-Shot Learning as Instruction Data Prospector for Large Language Models. ACL (1) (2024)
Zhengning Wu, Tianyu He, Xiaobo Xia, Jun Yu, Xu Shen, Tongliang Liu
Conditional Consistency Regularization for Semi-Supervised Multi-Label Image Classification. IEEE Trans. Multim. 26 (2024)
Jingyi Wang, Xiaobo Xia, Long Lan, Xinghao Wu, Jun Yu, Wenjing Yang, Bo Han, Tongliang Liu
Tackling Noisy Labels With Network Parameter Additive Decomposition. IEEE Trans. Pattern Anal. Mach. Intell. 46 (9) (2024)
Xiaobo Xia, Pengqian Lu, Chen Gong, Bo Han, Jun Yu, Jun Yu, Tongliang Liu
Regularly Truncated M-Estimators for Learning With Noisy Labels. IEEE Trans. Pattern Anal. Mach. Intell. 46 (5) (2024)
Shaokun Zhang, Xiaobo Xia, Zhaoqing Wang, Ling-Hao Chen, Jiale Liu, Qingyun Wu, Tongliang Liu
IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models. ICLR (2024)
Zhaoqing Wang, Xiaobo Xia, Ziye Chen, Xiao He, Yandong Guo, Mingming Gong, Tongliang Liu
Open-Vocabulary Segmentation with Unpaired Mask-Text Supervision. CoRR (2024)
Yiwei Zhou, Xiaobo Xia, Zhiwei Lin, Bo Han, Tongliang Liu
Few-Shot Adversarial Prompt Learning on Vision-Language Models. CoRR (2024)
Jingyi Wang, Xiaobo Xia, Long Lan, Xinghao Wu, Jun Yu, Wenjing Yang, Bo Han, Tongliang Liu
Tackling Noisy Labels with Network Parameter Additive Decomposition. CoRR (2024)
Run Luo, Yunshui Li, Longze Chen, Wanwei He, Ting-En Lin, Ziqiang Liu, Lei Zhang, Zikai Song, Xiaobo Xia, Tongliang Liu, Min Yang, Binyuan Hui
DEEM: Diffusion Models Serve as the Eyes of Large Language Models for Image Perception. CoRR (2024)
Yuhao Wu, Jiangchao Yao, Xiaobo Xia, Jun Yu, Ruxin Wang, Bo Han, Tongliang Liu
Mitigating Label Noise on Graph via Topological Sample Selection. CoRR (2024)
Xiaobo Xia, Jiankang Deng, Wei Bao, Yuxuan Du, Bo Han, Shiguang Shan, Tongliang Liu
Holistic Label Correction for Noisy Multi-Label Classification. ICCV (2023)
Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han
Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources. CoRR (2023)
Ling-Hao Chen, Yuanshuo Zhang, Taohua Huang, Liangcai Su, Zeyi Lin, Xi Xiao, Xiaobo Xia, Tongliang Liu
ERASE: Error-Resilient Representation Learning on Graphs for Label Noise Tolerance. CoRR (2023)
Xiu-Chuan Li, Xiaobo Xia, Fei Zhu, Tongliang Liu, Xu-Yao Zhang, Cheng-Lin Liu
Dynamics-aware loss for learning with label noise. Pattern Recognit. 144 (2023)
Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han
Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources. NeurIPS (2023)
Zhuo Huang, Xiaobo Xia, Li Shen, Bo Han, Mingming Gong, Chen Gong, Tongliang Liu
Harnessing Out-Of-Distribution Examples via Augmenting Content and Style. ICLR (2023)
Shikun Li, Xiaobo Xia, Hansong Zhang, Shiming Ge, Tongliang Liu
Multi-Label Noise Transition Matrix Estimation with Label Correlations: Theory and Algorithm. CoRR (2023)
Xiu-Chuan Li, Xiaobo Xia, Fei Zhu, Tongliang Liu, Xu-Yao Zhang, Cheng-Lin Liu
Dynamic-Aware Loss for Learning with Label Noise. CoRR (2023)
Zhuo Huang, Miaoxi Zhu, Xiaobo Xia, Li Shen, Jun Yu, Chen Gong, Bo Han, Bo Du, Tongliang Liu
Robust Generalization against Photon-Limited Corruptions via Worst-Case Sharpness Minimization. CoRR (2023)
Yong Lin, Renjie Pi, Weizhong Zhang, Xiaobo Xia, Jiahui Gao, Xiao Zhou, Tongliang Liu, Bo Han
A Holistic View of Label Noise Transition Matrix in Deep Learning and Beyond. ICLR (2023)
Xiaobo Xia, Bo Han, Yibing Zhan, Jun Yu, Mingming Gong, Chen Gong, Tongliang Liu
Combating Noisy Labels with Sample Selection by Mining High-Discrepancy Examples. ICCV (2023)
Jianing Qiu, Jian Wu, Hao Wei, Peilun Shi, Minqing Zhang, Yunyun Sun, Lin Li, Hanruo Liu, Hongyi Liu, Simeng Hou, Yuyang Zhao, Xuehui Shi, Junfang Xian, Xiaoxia Qu, Sirui Zhu, Lijie Pan, Xiaoniao Chen, Xiaojia Zhang, Shuai Jiang, Kebing Wang, Chenlong Yang, Mingqiang Chen, Sujie Fan, Jianhua Hu, Aiguo Lv, Hui Miao, Li Guo, Shujun Zhang, Cheng Pei, Xiaojuan Fan, Jianqin Lei, Ting Wei, Junguo Duan, Chun Liu, Xiaobo Xia, Siqi Xiong, Junhong Li, Benny Lo, Yih Chung Tham, Tien Yin Wong, Ningli Wang, Wu Yuan
VisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence. CoRR (2023)
Yuhao Wu, Xiaobo Xia, Jun Yu, Bo Han, Gang Niu, Masashi Sugiyama, Tongliang Liu
Making Binary Classification from Multiple Unlabeled Datasets Almost Free of Supervision. CoRR (2023)
Yunshui Li, Binyuan Hui, Xiaobo Xia, Jiaxi Yang, Min Yang, Lei Zhang, Shuzheng Si, Junhao Liu, Tongliang Liu, Fei Huang, Yongbin Li
One Shot Learning as Instruction Data Prospector for Large Language Models. CoRR (2023)
Zhuo Huang, Miaoxi Zhu, Xiaobo Xia, Li Shen, Jun Yu, Chen Gong, Bo Han, Bo Du, Tongliang Liu
Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization. CVPR (2023)
Ling-Hao Chen, Jiawei Zhang, Yewen Li, Yiren Pang, Xiaobo Xia, Tongliang Liu
HumanMAC: Masked Motion Completion for Human Motion Prediction. CoRR (2023)
Xiaobo Xia, Jiale Liu, Shaokun Zhang, Qingyun Wu, Tongliang Liu
Coreset Selection with Prioritized Multiple Objectives. CoRR (2023)
Xiaobo Xia, Jiale Liu, Jun Yu, Xu Shen, Bo Han, Tongliang Liu
Moderate Coreset: A Universal Method of Data Selection for Real-world Data-efficient Deep Learning. ICLR (2023)
Shaokun Zhang, Xiaobo Xia, Zhaoqing Wang, Ling-Hao Chen, Jiale Liu, Qingyun Wu, Tongliang Liu
IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models. CoRR (2023)
Xiaobo Xia, Pengqian Lu, Chen Gong, Bo Han, Jun Yu, Jun Yu, Tongliang Liu
Regularly Truncated M-estimators for Learning with Noisy Labels. CoRR (2023)
Xiaobo Xia, Bo Han, Nannan Wang, Jiankang Deng, Jiatong Li, Yinian Mao, Tongliang Liu
Extended $T$T: Learning With Mixed Closed-Set and Open-Set Noisy Labels. IEEE Trans. Pattern Anal. Mach. Intell. 45 (3) (2023)
Ling-Hao Chen, Jiawei Zhang, Yewen Li, Yiren Pang, Xiaobo Xia, Tongliang Liu
HumanMAC: Masked Motion Completion for Human Motion Prediction. ICCV (2023)
Shikun Li, Xiaobo Xia, Jiankang Deng, Shiming Ge, Tongliang Liu
Transferring Annotator- and Instance-dependent Transition Matrix for Learning from Crowds. CoRR (2023)
Shuo Yang, Peize Sun, Yi Jiang, Xiaobo Xia, Ruiheng Zhang, Zehuan Yuan, Changhu Wang, Ping Luo, Min Xu
Objects in Semantic Topology. ICLR (2022)
Shikun Li, Xiaobo Xia, Shiming Ge, Tongliang Liu
Selective-Supervised Contrastive Learning with Noisy Labels. CoRR (2022)
Zhengning Wu, Xiaobo Xia, Ruxin Wang, Jiatong Li, Jun Yu, Yinian Mao, Tongliang Liu
LR-SVM+: Learning Using Privileged Information with Noisy Labels. IEEE Trans. Multim. 24 (2022)
Xiaobo Xia, Wenhao Yang, Jie Ren, Yewen Li, Yibing Zhan, Bo Han, Tongliang Liu
Pluralistic Image Completion with Probabilistic Mixture-of-Experts. CoRR (2022)
Zhuo Huang, Xiaobo Xia, Li Shen, Bo Han, Mingming Gong, Chen Gong, Tongliang Liu
Harnessing Out-Of-Distribution Examples via Augmenting Content and Style. CoRR (2022)
Yewen Li, Chaojie Wang, Xiaobo Xia, Tongliang Liu, Xin Miao, Bo An
Out-of-Distribution Detection with An Adaptive Likelihood Ratio on Informative Hierarchical VAE. NeurIPS (2022)
Xiaobo Xia, Shuo Shan, Mingming Gong, Nannan Wang, Fei Gao, Haikun Wei, Tongliang Liu
Sample-Efficient Kernel Mean Estimator with Marginalized Corrupted Data. KDD (2022)
Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Jun Yu, Gang Niu, Masashi Sugiyama
Sample Selection with Uncertainty of Losses for Learning with Noisy Labels. ICLR (2022)
Shikun Li, Xiaobo Xia, Hansong Zhang, Yibing Zhan, Shiming Ge, Tongliang Liu
Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning. NeurIPS (2022)
Xiaobo Xia, Wenhao Yang, Jie Ren, Yewen Li, Yibing Zhan, Bo Han, Tongliang Liu
Pluralistic Image Completion with Gaussian Mixture Models. NeurIPS (2022)
Shikun Li, Xiaobo Xia, Shiming Ge, Tongliang Liu
Selective-Supervised Contrastive Learning with Noisy Labels. CVPR (2022)
Shijun Cai, Seok-Hee Hong, Xiaobo Xia, Tongliang Liu, Weidong Huang
A machine learning approach for predicting human shortest path task performance. Vis. Informatics 6 (2) (2022)
Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Jun Yu, Gang Niu, Masashi Sugiyama
Sample Selection with Uncertainty of Losses for Learning with Noisy Labels. CoRR (2021)
Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Jun Yu, Gang Niu, Masashi Sugiyama
Instance Correction for Learning with Open-set Noisy Labels. CoRR (2021)
Xiaobo Xia, Shuo Shan, Mingming Gong, Nannan Wang, Fei Gao, Haikun Wei, Tongliang Liu
Kernel Mean Estimation by Marginalized Corrupted Distributions. CoRR (2021)
Fei Long, Jing-Jie Peng, Weitao Song, Xiaobo Xia, Jun Sang
BloodCaps: A capsule network based model for the multiclassification of human peripheral blood cells. Comput. Methods Programs Biomed. 202 (2021)
Xiaobo Xia, Tongliang Liu, Bo Han, Chen Gong, Nannan Wang, Zongyuan Ge, Yi Chang
Robust early-learning: Hindering the memorization of noisy labels. ICLR (2021)
Xinrui Jiang, Nannan Wang, Jingwei Xin, Xiaobo Xia, Xi Yang, Xinbo Gao
Learning lightweight super-resolution networks with weight pruning. Neural Networks 144 (2021)
Shuo Yang, Peize Sun, Yi Jiang, Xiaobo Xia, Ruiheng Zhang, Zehuan Yuan, Changhu Wang, Ping Luo, Min Xu
Objects in Semantic Topology. CoRR (2021)
Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu
Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels. ICML (2021)
Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Mingming Gong, Haifeng Liu, Gang Niu, Dacheng Tao, Masashi Sugiyama
Part-dependent Label Noise: Towards Instance-dependent Label Noise. NeurIPS (2020)
Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu
Multi-Class Classification from Noisy-Similarity-Labeled Data. CoRR (2020)
Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Jiankang Deng, Jiatong Li, Yinian Mao
Extended T: Learning with Mixed Closed-set and Open-set Noisy Labels. CoRR (2020)
Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu
Class2Simi: A New Perspective on Learning with Label Noise. CoRR (2020)
Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Mingming Gong, Haifeng Liu, Gang Niu, Dacheng Tao, Masashi Sugiyama
Parts-dependent Label Noise: Towards Instance-dependent Label Noise. CoRR (2020)
Xiaobo Xia, Tongliang Liu, Nannan Wang, Bo Han, Chen Gong, Gang Niu, Masashi Sugiyama
Are Anchor Points Really Indispensable in Label-Noise Learning? NeurIPS (2019)
Xiaobo Xia, Tongliang Liu, Nannan Wang, Bo Han, Chen Gong, Gang Niu, Masashi Sugiyama
Are Anchor Points Really Indispensable in Label-Noise Learning? CoRR (2019)