Author

Yingfan Liu

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Preprint Aug 2026

Efficient Privacy-Preserving Range Filtered Approximate Nearest Neighbor Search

This is the first study that systematically formulates and evaluates privacy-preserving RFANNS over outsourced encrypted vector databases, and improves the QPS-Recall trade-off over representative secure adaptations of existing RFANNS approaches, scaling effectively to large datasets.

Haoyu Wang, Yandi Zhang, Jia-Dong Xie et al. · 0 citations

Preprint Aug 2026

FROG: Efficient Range-Filtering Approximate Nearest Neighbor Search on GPUs

FROG is a GPU-oriented RFANNS index that replaces multiple locally optimal substructure building with a globally aware, vertex-centric design and organizes diverse expansion neighbor candidates for each vertex in a GPU-friendly structure and rapidly identifies the expansion neighbors used for computation at query time.

Xiao-Kun Cui, Peng Liu, Jia-Dong Xie et al. · 0 citations

Preprint Aug 2026

Efficient Coreset Selection via K-Nearest Neighbor Graphs

Experiments show that KNNG-CS achieves accuracy comparable to representative gradient-approximation coreset methods, while reducing selection time by $2.3\times$-$41.2\times$ and peak memory to $0.3\%$-$7.5\%$ of the baselines.

Yingfan Liu, Lei-Yu Zhang, Jia-Dong Xie et al. · 1 citation