Xu, Ming

20 publications

ICLR 2025 BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions Terry Yue Zhuo, Vu Minh Chien, Jenny Chim, Han Hu, Wenhao Yu, Ratnadira Widyasari, Imam Nur Bani Yusuf, Haolan Zhan, Junda He, Indraneil Paul, Simon Brunner, Chen Gong, James Hoang, Armel Randy Zebaze, Xiaoheng Hong, Wen-Ding Li, Jean Kaddour, Ming Xu, Zhihan Zhang, Prateek Yadav, Naman Jain, Alex Gu, Zhoujun Cheng, Jiawei Liu, Qian Liu, Zijian Wang, Binyuan Hui, Niklas Muennighoff, David Lo, Daniel Fried, Xiaoning Du, Harm de Vries, Leandro Von Werra

ICML 2025 Can We Predict Performance of Large Models Across Vision-Language Tasks? Qinyu Zhao, Ming Xu, Kartik Gupta, Akshay Asthana, Liang Zheng, Stephen Gould

NeurIPS 2025 ObCLIP: Oblivious CLoud-Device Hybrid Image Generation with Privacy Preservation Haoqi Wu, Wei Dai, Ming Xu, Wang Li, Qiang Yan

NeurIPS 2024 Molecule Design by Latent Prompt Transformer Deqian Kong, Yuhao Huang, Jianwen Xie, Edouardo Honig, Ming Xu, Shuanghong Xue, Pei Lin, Sanping Zhou, Sheng Zhong, Nanning Zheng, Ying Nian Wu

CVPR 2024 Temporally Consistent Unbalanced Optimal Transport for Unsupervised Action Segmentation Ming Xu, Stephen Gould

ECCV 2024 The First to Know: How Token Distributions Reveal Hidden Knowledge in Large Vision-Language Models? Qinyu Zhao, Ming Xu, Kartik Gupta, Akshay Asthana, Liang Zheng, Stephen Gould

ICLR 2024 Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection Qinyu Zhao, Ming Xu, Kartik Gupta, Akshay Asthana, Liang Zheng, Stephen Gould

ECCV 2024 VLAD-BuFF: Burst-Aware Fast Feature Aggregation for Visual Place Recognition Ahmad Khaliq, Ming Xu, Stephen Hausler, Michael J Milford, Sourav Garg

ICLR 2023 Deep Declarative Dynamic Time Warping for End-to-End Learning of Alignment Paths Ming Xu, Sourav Garg, Michael Milford, Stephen Gould

IJCAI 2023 Deep Unfolding Convolutional Dictionary Model for Multi-Contrast MRI Super-Resolution and Reconstruction Pengcheng Lei, Faming Fang, Guixu Zhang, Ming Xu

NeurIPS 2023 Revisiting Implicit Differentiation for Learning Problems in Optimal Control Ming Xu, Timothy L. Molloy, Stephen Gould

ICMLW 2023 Towards Understanding Gradient Approximation in Equality Constrained Deep Declarative Networks Stephen Gould, Ming Xu, Zhiwei Xu, Yanbin Liu

AAAI 2023 Two Wrongs Don't Make a Right: Combating Confirmation Bias in Learning with Label Noise Mingcai Chen, Hao Cheng, Yuntao Du, Ming Xu, Wenyu Jiang, Chongjun Wang

ECCV 2022 3D Random Occlusion and Multi-Layer Projection for Deep Multi-Camera Pedestrian Localization Rui Qiu, Ming Xu, Yuyao Yan, Jeremy S. Smith, Xi Yang

CVPR 2022 FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correction Liang Gao, Huazhu Fu, Li Li, Yingwen Chen, Ming Xu, Cheng-Zhong Xu

CoRL 2022 Residual Skill Policies: Learning an Adaptable Skill-Based Action Space for Reinforcement Learning for Robotics Krishan Rana, Ming Xu, Brendan Tidd, Michael Milford, Niko Suenderhauf

CVPR 2021 Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition Stephen Hausler, Sourav Garg, Ming Xu, Michael Milford, Tobias Fischer

AISTATS 2019 Variance Reduction Properties of the Reparameterization Trick Ming Xu, Matias Quiroz, Robert Kohn, Scott A. Sisson

CVPRW 2015 Channel-Max, Channel-Drop and Stochastic Max-Pooling Yuchi Huang, Xiuyu Sun, Ming Lu, Ming Xu

ECML-PKDD 2009 A Fast Ensemble Pruning Algorithm Based on Pattern Mining Process Qiang-Li Zhao, Yan-Huang Jiang, Ming Xu