Ning Ding

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I received my Ph.D. at the Department of Computer Science and Technology, Tsinghua Univeristy in 2023, advised by Prof. Hai-Tao Zheng and also co-advised by Prof. Zhiyuan Liu.


My research spans the areas of natural language processing and machine learning. At the current stage, I am particularly interested advanced stimulation of language models. My research aims to develop theory, tools, and algorithms to effectively and efficiently drive language models (especially the large ones), and also establish a deeper understanding by observing the behaviors of models.

Selected Papers

  1. Parameter-efficient Fine-tuning of Large-scale Pre-trained Language Models
    Ning Ding, Yujia Qin, Guang Yang, Fuchao Wei, Zonghan Yang, Yusheng Su, Shengding Hu, Yulin Chen, Chi-Min Chan, Weize Chen, Jing Yi, Weilin Zhao, Zhiyuan Liu, Hai-Tao Zheng, Jianfei Chen, Yang Liu, Jie Tang, Juanzi Li, and Maosong Sun
    Nature Machine Intelligence
    Cover Article of Nature Machine Intelligenceā€™s March Issue
    World Artificial Intelligence Conference Youth Outstanding Paper Award
  2. Enhancing Chat Language Models by Scaling High-quality Instructional Conversations
    Ning Ding, Yulin Chen, Bokai Xu, Yujia Qin, Shengding Hu, Zhiyuan Liu, Maosong Sun, and Bowen Zhou
    EMNLP 2023
  3. OpenPrompt: An Open-source Framework for Prompt-learning
    Ning Ding, Shengding Hu, Weilin Zhao, Yulin Chen, Zhiyuan Liu, Hai-Tao Zheng, and Maosong Sun
    ACL System Demonstration 2022
    Best Demo Paper Award
  4. Few-NERD: A Few-shot Named Entity Recognition Dataset
    Ning Ding, Guangwei Xu, Yulin Chen, Xiaobin Wang, Xu Han, Pengjun Xie, Hai-Tao Zheng, and Zhiyuan Liu
    ACL 2021
    Oral Presentation
  5. Prototypical Representation Learning for Relation Extraction
    Ning Ding, Xiaobin Wang, Yao Fu, Guangwei Xu, Rui Wang, Pengjun Xie, Ying Shen, Fei Huang, Hai-Tao Zheng, and Rui Zhang
    International Conference on Learning Representations,

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