collaborators

5 papers

cs.DB2026

CLIP: Lightweight Cosine-Law-Based Inverted-List Pruning for IVF-Based Vector Search

Yitong Song, Shuhang Lu, Xuanhe Zhou +2

Vector search has become a core component of modern multimodal retrieval systems. Among existing methods, inverted file (IVF)-based methods are widely adopted due to their scalabil…

cs.DB2026

HIRE: A Hybrid Learned Index for Robust and Efficient Performance under Mixed Workloads

Xinyi Zhang, Liang Liang, Anastasia Ailamaki +1

Indexes are critical for efficient data retrieval and updates in modern databases. Recent advances in machine learning have led to the development of learned indexes, which model t…

cs.DB2026

BAMG: A Block-Aware Monotonic Graph Index for Disk-Based Approximate Nearest Neighbor Search

Huiling Li, Xin Huang, Byron Choi +1

Approximate Nearest Neighbor Search (ANNS) over high-dimensional vectors is a foundational problem in databases, where disk I/O often emerges as the dominant performance bottleneck…

cs.DB2026

Vector Search for the Future: From Memory-Resident, Static Heterogeneous Storage, to Cloud-Native Architectures

Yitong Song, Xuanhe Zhou, Christian S. Jensen +1

Vector search (VS) has become a fundamental component in multimodal data management, enabling core functionalities such as image, video, and code retrieval. As vector data scales r…

cs.LG2025

Skeleton-Guided Learning for Shortest Path Search

Tiantian Liu, Xiao Li, Huan Li +3

Shortest path search is a core operation in graph-based applications, yet existing methods face important limitations. Classical algorithms such as Dijkstra's and A* become ineffic…