About Me

I’m currently a first year PhD at HKUST (GZ), surpervised by Prof Enyan DAI. Prior to this, I obtained my master’s degree from Fudan University, where I specialized in Natural Language Processing under the guidance of Professor Xiaoqing ZHENG in the FudanNLP Lab. My current research interests focus on Trustworthy LLMs, foundational models, and AI for Science.

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Interests
  • Artificial Intelligence
  • Large Language Models
  • AI for Science
Education
  • PhD Artificial Intelligence

    The Hong Kong University of Science and Technology (Guangzhou)

  • MEng Artificial Intelligence

    Fudan University

  • BSc Mathematics and Applied Mathematics

    Shanghai University

📚 My Research

I’m a first year PhD at HKUST (GZ). Currently, my research focuses on two main areas.

The first area is Trustworthy AI. Specifically, I aim to design algorithms capable of extracting the “fingerprint” of large language models (LLMs) to protect their intellectual property. I am also exploring privacy issues in multi-agent systems and investigating LLMs unlearning problems.

The second area is AI4Science, where I hope to train high-performing foundational models applicable to a wide range of protein-related tasks. Additionally, I seek to explore methods for seamlessly integrating graph modalities with LLMs to enhance the model’s ability to understand and represent protein structures and semantic information.

I’m a complete beginner, but if any experts are interested, please feel free to reach out to collaborate 😃

Selected Publications
Recent Publications
(2024). ChemLLM: A Chemical Large Language Model.
(2023). Hallucination detection for generative large language models by bayesian sequential estimation. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing.
(2023). Measure Children’s Mindreading Ability with Machine Reading. In Findings of the Association for Computational Linguistics, EMNLP 2023.
Recent & Upcoming Talks
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