Zheng Xu (许正)

Zheng is a research scientist working on federated learning and privacy. He got his PhD on optimization and machine learning from University of Maryland, College Park. More information can be found in google scholar and github.
Authored Publications
Sort By
  • Title
  • Title, descending
  • Year
  • Year, descending
    InstructPipe: Generating Visual Blocks Pipelines with Human Instructions and LLMs
    Jing Jin
    Xiuxiu Yuan
    Jun Jiang
    Jingtao Zhou
    Yiyi Huang
    Kristen Wright
    Jason Mayes
    Mark Sherwood
    Johnny Lee
    Alex Olwal
    Ram Iyengar
    Na Li
    Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI), ACM, pp. 23
    Experiencing InstructPipe: Building Multi-modal AI Pipelines via Prompting LLMs and Visual Programming
    Jing Jin
    Xiuxiu Yuan
    Jun Jiang
    Jingtao Zhou
    Yiyi Huang
    Kristen Wright
    Jason Mayes
    Mark Sherwood
    Johnny Lee
    Alex Olwal
    Ram Iyengar
    Na Li
    Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems, ACM, pp. 5
    Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models
    Yae Jee Cho
    Aldi Fahrezi
    Gauri Joshi
    The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024) (2024)
    Privacy-Preserving Instructions for Aligning Large Language Models
    Da Yu
    Sewoong Oh
    International Conference on Machine Learning (ICML) (2024)
    Efficient Language Model Architectures for Differentially Private Federated Learning
    Yanxiang Zhang
    Privacy Regulation and Protection in Machine Learning Workshop at ICLR 2024 (2024) (to appear)
    Federated Learning of Gboard Language Models with Differential Privacy
    Yanxiang Zhang
    Galen Andrew
    Jesse Rosenstock
    Yuanbo Zhang
    ACL industry track (2023) (to appear)
    On the Convergence of Federated Averaging with Cyclic Client Participation
    Yae Jee Cho
    Pranay Sharma
    Gauri Joshi
    Satyen Kale
    Tong Zhang
    International Conference on Machine Learning (ICML) (2023) (to appear)
    Learning to Generate Image Embeddings with User-level Differential Privacy
    Maxwell D. Collins
    Yuxiao Wang
    Sewoong Oh
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2023) (to appear)