About me

I am now a Ph.D. candidate in the College of Computer Science and Technology at Hangzhou Dianzi University. I enjoy working with labmates of KGLab. My current research focuses on the management and analyses of high-dimensional data, including:

• Graph-based vector indexing for approximate nearest neighbor search
• Multi-modal retrieval and analyses
• High-dimensional data storage and compression
• Vector database and its AI applications (e.g., Retrieval-Augmented Generation (RAG))

Publications

• Q Yue, X Xu, Y Wang, Y Tao, X Luo. Routing-Guided Learned Product Quantization for Graph-Based Approximate Nearest Neighbor Search (ICDE), 2024.
• M Wang, X Xu, Q Yue, Y Wang. A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search (VLDB), 2021.
• M Wang, L Lv, X Xu, Y Wang, Q Yue, J Ni. An Efficient and Robust Framework for Approximate Nearest Neighbor Search with Attribute Constraint (NeurIPS), 2023.
• Q Yue, M Wang, X Xu, J Wang. A Robust Framework for Out-of-Distribution Vector Similarity Search (SIGMOD), to be submitted.
• X Luo, Q Yue, X Xu. NUBIT : Effective Non-Uniform Product Quantization with Theoretical Distortion Bound (VLDB), to be submitted.