I am currently a master’s student at the Institute of Computing Technology, Chinese Academy of Sciences, with a research focus on representation learning and information retrieval. I am passionate about exploring fundamental challenges in Natural Language Processing and related areas. I possess strong self-learning capabilities, solid research and engineering practice experience, effective communication skills, and a positive, collaborative attitude. I have also accumulated rich research experience through participation in multiple academic projects.
M.Eng Artificial Intelligence
University of Chinese Academy of Sciences
B.Eng Artificial Intelligence
Beijing University of Posts and Telecommunications
My current research interests focus on representation learning and information retrieval, within the broader area of natural language processing.
I am dedicated to developing innovative methods for building more effective and robust representations, and advancing retrieval techniques to better support real-world applications.
Feel free to reach out if you’re interested in collaboration! 😃
Generative LLM have achieved remarkable success in various industrial applications, owing to their promising In-Context Learning capabilities. However, the issue of long context in …
With the extensive use of large language models, automatically generating QA datasets for domain-specific fine-tuning has become crucial. However, considering the multifaceted …
Our paper “QUITO-X: A New Perspective on Context Compression from the Information Bottleneck Theory” has been accepted by EMNLP 2025! 🎉
Our paper “MDPO: Customized Direct Preference Optimization with a Metric-based Sampler for Question and Answer Generation” has been accepted by COLING 2025! 🎉
