Dr Zihao Fu

Research Associate

Contact information

Biography

I am a Research Associate (PostDoc) in the Language Technology Lab, University of Cambridge working with Prof. Nigel Collier. My research mainly focuses on Natural Language Processing, Text Generation, Machine Learning, Biomedical Applications, and etc. Before I came to Cambridge, I received my Ph.D. degree from The Chinese University of Hong Kong under the supervision of Prof. Wai Lam. I have also been a visiting student at the NLP Lab of Tsinghua University, working with Prof. Zhiyuan Liu. Before I started my Ph.D. study, I have three years of experience in developing large-scale distributed parallel algorithms for the PAI platform in Alibaba Cloud.

Research interests

Natural Language Processing: Large Language Models, Text Generation, Biomedical NLP, Named Entity Recognition, Knowledge Integration

Machine Learning: Stability Analysis, PAC Theory, Explainable Machine Learning, Language Model Analysis, Regularization, Optimization

Biomedical Applications: Digital Health, Disease Surveillance, Epidemiology

Publications

Zihao Fu, Anthony Man-Cho So, Nigel Collier. A Stability Analysis of Fine-Tuning a Pre-Trained Model. PrePrint
Zihao Fu, Wai Lam, Qian Yu, Anthony Man-Cho So, Shengding Hu, Zhiyuan Liu, Nigel Collier. Decoder-Only or Encoder-Decoder? Interpreting Language Model as a Regularized Encoder-Decoder. PrePrint
Zihao Fu, Haoran Yang, Anthony Man-Cho So, Wai Lam, Lidong Bing, Nigel Collier. On the Effectiveness of Parameter-Efficient Fine-Tuning. The 37th AAAI Conference on Artificial Intelligence (AAAI 2023).
Zihao Fu. Open Domain Text Generation. (PhD Thesis, The Chinese University of Hong Kong, 2021).
Zihao Fu, Wai Lam, Anthony Man-Cho So, Bei Shi. A Theoretical Analysis of the Repetition Problem in Text Generation. The 35th AAAI Conference on Artificial Intelligence (AAAI 2021).
Zihao Fu, Lidong Bing, Wai Lam. Open Domain Event Text Generation. The 34th AAAI Conference on Artificial Intelligence (AAAI 2020).
Zihao Fu, Bei Shi, Wai Lam, Lidong Bing, Zhiyuan Liu. Partially-Aligned Data-to-Text Generation with Distant Supervision. The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020).
Zihao Fu, Lidong Bing, Wai Lam, Shoaib Jameel. Dynamic Topic Tracker for KB-to-Text Generation. The 28th International Conference on Computational Linguistics (COLING 2020).
Zihao Fu, Bei Shi, Lidong Bing, Wai Lam. Unsupervised KB-to-Text Generation with Auxiliary Triple Extraction using Dual Learning. The 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing (AACL-IJCNLP 2020).
Zihao Fu, Yankai Lin, Zhiyuan Liu, Wai Lam. Fact Discovery from Knowledge Base via Facet Decomposition. The 2019 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT 2019).
Shoaib Jameel, Zihao Fu, Bei Shi, Wai Lam, Steven Schockaert. Word Embedding as Maximum A Posteriori Estimation. The 33rd AAAI Conference on Artificial Intelligence (AAAI 2019).
Bei Shi, Zihao Fu, Lidong Bing, Wai Lam. Learning Domain-Sensitive and Sentiment-Aware Word Embeddings. The 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018).
Guo, Tszhang, Bowen Li, Zihao Fu, Tao Wan and Zengchang Qin. Learning Sentimental Weights of Mixed-gram Terms for Classification and Visualization. Pacific Rim International Conferences on Artificial Intelligence (PRICAI 2016).
Yanan Zhou, Zihao Fu, Guanghong Gong. Pilot Behavior Modeling Using LSTM Network: A Case Study. Asian Simulation Conference (ASC 2016).
Zihao Fu, Guanghong Gong. Explicit moment integration algorithm and its application. Journal of Beijing University of Aeronautics and Astronautics (JBUAA 2015).
Zihao Fu. Research on the Optimization Methods of the Blended-Wing-Body Aircraft. (Master Thesis 2015).

About us

The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science and AI. C2D3 is an Interdisciplinary Research Centre at the University of Cambridge.

  • Supports and connects the growing data science and AI research community 
  • Builds research capacity in data science and AI to tackle complex issues 
  • Drives new research challenges through collaborative research projects 
  • Promotes and provides opportunities for knowledge transfer 
  • Identifies and provides training courses for students, academics, industry and the third sector 
  • Serves as a gateway for external organisations 

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