World's Best Scientists 2026 revealed!
Hai-Tao Zheng

Hai-Tao Zheng

Overview

Hai-Tao Zheng is affiliated with Tsinghua University in China. Their research primarily focuses on the field of Computer Science, with extensive work in several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications, and Signal Processing.

The scientist has contributed to research covering multiple key topics:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Text Readability and Simplification
  • Domain Adaptation and Few-Shot Learning
  • Advanced Graph Neural Networks
  • Adversarial Robustness in Machine Learning

Hai-Tao Zheng has published extensively, with a notable presence in prominent academic venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • SSRN Electronic Journal
  • IEEE Transactions on Knowledge and Data Engineering
  • 2022 International Joint Conference on Neural Networks (IJCNN)

Their recent papers illustrate a diverse research scope and collaboration with other scholars. Selected recent works include:

  • "Parameter-efficient fine-tuning of large-scale pre-trained language models," 2023, Nature Machine Intelligence
  • "Modeling Relation Paths for Knowledge Graph Completion," 2020, IEEE Transactions on Knowledge and Data Engineering
  • "Are we ready for a new paradigm shift? A survey on visual deep MLP," 2022, Patterns
  • "The effect of institutional ownership on listed companies' tax avoidance strategies," 2020, Applied Economics
  • "OpenPrompt: An Open-source Framework for Prompt-learning," 2021, arXiv (Cornell University)

Hai-Tao Zheng frequently collaborates with a number of co-authors. Among the most frequent are:

  • Yangning Li
  • Yinghui Li
  • Ying Shen
  • Ben Y. Zhao
  • Shirong Ma

Best Publications

  • ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design

    Ningning Ma;Xiangyu Zhang;Hai-Tao Zheng;Jian Sun

  • Parameter-efficient fine-tuning of large-scale pre-trained language models

    Unknown

  • Few-NERD: A Few-shot Named Entity Recognition Dataset

    Ning Ding;Guangwei Xu;Yulin Chen;Xiaobin Wang

  • OpenPrompt: An Open-source Framework for Prompt-learning

    Ning Ding;Shengding Hu;Weilin Zhao;Yulin Chen

  • Modeling Relation Paths for Knowledge Graph Completion

    Ying Shen;Ning Ding;Hai-Tao Zheng;Yaliang Li

  • Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models

    Unknown

  • Exploiting noun phrases and semantic relationships for text document clustering

    Hai-Tao Zheng;Bo-Yeong Kang;Hong-Gee Kim

  • Applying policy network theory to policy-making in China: the case of urban health insurance reform.

    Haitao Zheng;Martin De Jong;Joop Koppenjan

  • Prompt-Learning for Fine-Grained Entity Typing.

    Ning Ding;Yulin Chen;Xu Han;Guangwei Xu

  • An ontology-based approach to learnable focused crawling

    Hai-Tao Zheng;Bo-Yeong Kang;Hong-Gee Kim

  • CLINE: Contrastive Learning with Semantic Negative Examples for Natural Language Understanding

    Dong Wang;Ning Ding;Piji Li;Haitao Zheng

  • Byte Segment Neural Network for Network Traffic Classification

    Rui Li;Xi Xiao;Shiguang Ni;Haitao Zheng

  • Chinese Relation Extraction with Multi-Grained Information and External Linguistic Knowledge.

    Ziran Li;Ning Ding;Zhiyuan Liu;Haitao Zheng

  • An Ontology-Based Bayesian Network Approach for Representing Uncertainty in Clinical Practice Guidelines

    Hai-Tao Zheng;Bo-Yeong Kang;Hong-Gee Kim

  • EBSNN: Extended Byte Segment Neural Network for Network Traffic Classification

    Xi Xiao;Wentao Xiao;Rui Li;Xiapu Luo

  • A semantic similarity measure based on information distance for ontology alignment

    Yong Jiang;Xinmin Wang;Hai-Tao Zheng

  • Event Detection with Trigger-Aware Lattice Neural Network.

    Ning Ding;Ziran Li;Zhiyuan Liu;Haitao Zheng

  • MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation

    Unknown

  • Deterministic Constructions of Binary Measurement Matrices From Finite Geometry

    Shu-Tao Xia;Xin-Ji Liu;Yong Jiang;Hai-Tao Zheng

  • Clickbait Convolutional Neural Network

    Hai-Tao Zheng;Jin-Yuan Chen;Xin Yao;Arun Kumar Sangaiah

  • Prototypical Representation Learning for Relation Extraction

    Ning Ding;Xiaobin Wang;Yao Fu;Guangwei Xu

  • The World is Not Binary: Learning to Rank with Grayscale Data for Dialogue Response Selection

    Zibo Lin;Deng Cai;Yan Wang;Xiaojiang Liu

  • TRSDL: Tag-Aware Recommender System Based on Deep Learning–Intelligent Computing Systems

    Nan Liang;Hai-Tao Zheng;Jin-Yuan Chen;Arun Kumar Sangaiah

  • Sparks and Deterministic Constructions of Binary Measurement Matrices from Finite Geometry

    Shu-Tao Xia;Xin-Ji Liu;Yong Jiang;Hai-Tao Zheng

Frequent Co-Authors

Arun Kumar Sangaiah
Arun Kumar Sangaiah National Yunlin University of Science and Technology
Ying Shen
Ying Shen Sun Yat-sen University
Yaliang Li
Yaliang Li Alibaba Group (China)
Dong Wang
Dong Wang Dalian University of Technology
Rui Zhang
Rui Zhang National University of Singapore
Juanzi Li
Juanzi Li Tsinghua University
Shuming Shi
Shuming Shi Tencent (China)
Jian Sun
Jian Sun Megvii
Xiapu Luo
Xiapu Luo Hong Kong Polytechnic University

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