Xia, Xiaobo

33 publications

NeurIPS 2025 Continual Multimodal Contrastive Learning Xiaohao Liu, Xiaobo Xia, See-Kiong Ng, Tat-Seng Chua

ICLR 2025 DEEM: Diffusion Models Serve as the Eyes of Large Language Models for Image Perception Run Luo, Yunshui Li, Longze Chen, Wanwei He, Ting-En Lin, Ziqiang Liu, Lei Zhang, Zikai Song, Hamid Alinejad-Rokny, Xiaobo Xia, Tongliang Liu, Binyuan Hui, Min Yang

ICML 2025 DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Zhenglin Zhou, Xiaobo Xia, Fan Ma, Hehe Fan, Yi Yang, Tat-Seng Chua

AAAI 2025 Hierarchical Context Pruning: Optimizing Real-World Code Completion with Repository-Level Pretrained Code LLMs Lei Zhang, Yunshui Li, Jiaming Li, Xiaobo Xia, Jiaxi Yang, Run Luo, Minzheng Wang, Longze Chen, Junhao Liu, Qiang Qu, Min Yang

NeurIPS 2025 L-MTP: Leap Multi-Token Prediction Beyond Adjacent Context for Large Language Models Xiaohao Liu, Xiaobo Xia, Weixiang Zhao, Manyi Zhang, Xianzhi Yu, Xiu Su, Shuo Yang, See-Kiong Ng, Tat-Seng Chua

CVPR 2025 LaVin-DiT: Large Vision Diffusion Transformer Zhaoqing Wang, Xiaobo Xia, Runnan Chen, Dongdong Yu, Changhu Wang, Mingming Gong, Tongliang Liu

NeurIPS 2025 OpenOmni: Advancing Open-Source Omnimodal Large Language Models with Progressive Multimodal Alignment and Real-Time Emotional Speech Synthesis Run Luo, Ting-En Lin, Haonan Zhang, Yuchuan Wu, Xiong Liu, Yongbin Li, Longze Chen, Jiaming Li, Lei Zhang, Xiaobo Xia, Hamid Alinejad-Rokny, Fei Huang, Min Yang

NeurIPS 2025 UtilGen: Utility-Centric Generative Data Augmentation with Dual-Level Task Adaptation Jiyu Guo, Shuo Yang, Yiming Huang, Yancheng Long, Xiaobo Xia, Xiu Su, Bo Zhao, Zeke Xie, Liqiang Nie

NeurIPS 2025 VCM: Vision Concept Modeling with Adaptive Vision Token Compression via Instruction Fine-Tuning Run Luo, Renke Shan, Longze Chen, Ziqiang Liu, Lu Wang, Min Yang, Xiaobo Xia

ICCV 2025 Where, What, Why: Towards Explainable Driver Attention Prediction Yuchen Zhou, Jiayu Tang, Xiaoyan Xiao, Yueyao Lin, Linkai Liu, Zipeng Guo, Hao Fei, Xiaobo Xia, Chao Gou

NeurIPS 2024 Few-Shot Adversarial Prompt Learning on Vision-Language Models Yiwei Zhou, Xiaobo Xia, Zhiwei Lin, Bo Han, Tongliang Liu

ICLR 2024 IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models Shaokun Zhang, Xiaobo Xia, Zhaoqing Wang, Ling-Hao Chen, Jiale Liu, Qingyun Wu, Tongliang Liu

ICML 2024 Mitigating Label Noise on Graphs via Topological Sample Selection Yuhao Wu, Jiangchao Yao, Xiaobo Xia, Jun Yu, Ruxin Wang, Bo Han, Tongliang Liu

ICML 2024 Refined Coreset Selection: Towards Minimal Coreset Size Under Model Performance Constraints Xiaobo Xia, Jiale Liu, Shaokun Zhang, Qingyun Wu, Hongxin Wei, Tongliang Liu

ICML 2024 Towards Realistic Model Selection for Semi-Supervised Learning Muyang Li, Xiaobo Xia, Runze Wu, Fengming Huang, Jun Yu, Bo Han, Tongliang Liu

ICLR 2023 A Holistic View of Label Noise Transition Matrix in Deep Learning and Beyond Lin Yong, Renjie Pi, Weizhong Zhang, Xiaobo Xia, Jiahui Gao, Xiao Zhou, Tongliang Liu, Bo Han

ICCV 2023 Combating Noisy Labels with Sample Selection by Mining High-Discrepancy Examples Xiaobo Xia, Bo Han, Yibing Zhan, Jun Yu, Mingming Gong, Chen Gong, Tongliang Liu

ICLR 2023 Harnessing Out-of-Distribution Examples via Augmenting Content and Style Zhuo Huang, Xiaobo Xia, Li Shen, Bo Han, Mingming Gong, Chen Gong, Tongliang Liu

ICCV 2023 Holistic Label Correction for Noisy Multi-Label Classification Xiaobo Xia, Jiankang Deng, Wei Bao, Yuxuan Du, Bo Han, Shiguang Shan, Tongliang Liu

ICCV 2023 HumanMAC: Masked Motion Completion for Human Motion Prediction Ling-Hao Chen, JiaWei Zhang, Yewen Li, Yiren Pang, Xiaobo Xia, Tongliang Liu

ICLR 2023 Moderate Coreset: A Universal Method of Data Selection for Real-World Data-Efficient Deep Learning Xiaobo Xia, Jiale Liu, Jun Yu, Xu Shen, Bo Han, Tongliang Liu

NeurIPS 2023 Out-of-Distribution Detection Learning with Unreliable Out-of-Distribution Sources Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han

CVPR 2023 Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization Zhuo Huang, Miaoxi Zhu, Xiaobo Xia, Li Shen, Jun Yu, Chen Gong, Bo Han, Bo Du, Tongliang Liu

NeurIPS 2022 Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning Shikun Li, Xiaobo Xia, Hansong Zhang, Yibing Zhan, Shiming Ge, Tongliang Liu

ICLR 2022 Objects in Semantic Topology Shuo Yang, Peize Sun, Yi Jiang, Xiaobo Xia, Ruiheng Zhang, Zehuan Yuan, Changhu Wang, Ping Luo, Min Xu

NeurIPS 2022 Out-of-Distribution Detection with an Adaptive Likelihood Ratio on Informative Hierarchical VAE Yewen Li, Chaojie Wang, Xiaobo Xia, Tongliang Liu, Xin Miao, Bo An

NeurIPS 2022 Pluralistic Image Completion with Gaussian Mixture Models Xiaobo Xia, Wenhao Yang, Jie Ren, Yewen Li, Yibing Zhan, Bo Han, Tongliang Liu

ICLR 2022 Sample Selection with Uncertainty of Losses for Learning with Noisy Labels Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Jun Yu, Gang Niu, Masashi Sugiyama

CVPR 2022 Selective-Supervised Contrastive Learning with Noisy Labels Shikun Li, Xiaobo Xia, Shiming Ge, Tongliang Liu

ICML 2021 Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu

ICLR 2021 Robust Early-Learning: Hindering the Memorization of Noisy Labels Xiaobo Xia, Tongliang Liu, Bo Han, Chen Gong, Nannan Wang, Zongyuan Ge, Yi Chang

NeurIPS 2020 Part-Dependent Label Noise: Towards Instance-Dependent Label Noise Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Mingming Gong, Haifeng Liu, Gang Niu, Dacheng Tao, Masashi Sugiyama

NeurIPS 2019 Are Anchor Points Really Indispensable in Label-Noise Learning? Xiaobo Xia, Tongliang Liu, Nannan Wang, Bo Han, Chen Gong, Gang Niu, Masashi Sugiyama