8 citations · 9 across the 11 of their papers we have counts for
13 papers
PiLLar: Matching for Pivot Table Schema via LLM-guided Monte-Carlo Tree Search
Yunjun Gao, Chuangyu Ouyang, Congcong Ge +1
Pivot tables are ubiquitous in data lakes of modern data ecosystems, making accurate schema matching over pivot tables a key prerequisite for data integration. In this paper, we fo…
A GPU-Accelerated Framework for Multi-Attribute Range Filtered Approximate Nearest Neighbor Search
Zhonggen Li, Haoran Yu, Zixuan Xu +2
Range-filtered approximate nearest neighbor search (RFANNS) is increasingly critical for modern vector databases. However, existing solutions suffer from severe index inflation and…
All-in-one Graph-based Indexing for Hybrid Search on GPUs
Zhonggen Li, Yougen Li, Yifan Zhu +3
Hybrid search has emerged as a promising paradigm that combines lexical and semantic retrieval, enhancing accuracy for applications such as recommendations, information retrieval,…
MontePrep: Monte-Carlo-Driven Automatic Data Preparation without Target Data Instances
Congcong Ge, Yachuan Liu, Yixuan Tang +3
In commercial systems, a pervasive requirement for automatic data preparation (ADP) is to transfer relational data from disparate sources to targets with standardized schema specif…
Scalable Graph Indexing using GPUs for Approximate Nearest Neighbor Search
Zhonggen Li, Xiangyu Ke, Yifan Zhu +3
Approximate nearest neighbor search (ANNS) in high-dimensional vector spaces has a wide range of real-world applications. Numerous methods have been proposed to handle ANNS efficie…
Accelerating High-Dimensional Nearest Neighbor Search with Dynamic Query Preference
Yifan Zhu, Ruijie Zhao, Zhonggen Li +4
Approximate Nearest Neighbor Search (ANNS) has emerged as an essential operation in modern database and AI systems. While graph-based methods like NSG demonstrate state-of-the-art…
Balancing the Blend: An Experimental Analysis of Trade-offs in Hybrid Search
Mengzhao Wang, Boyu Tan, Yunjun Gao +5
Hybrid search, the integration of lexical and semantic retrieval, has become a cornerstone of modern information retrieval systems, driven by demanding applications like Retrieval-…
OneDB: A Distributed Multi-Metric Data Similarity Search System
Tang Qian, Yifan Zhu, Lu Chen +5
Increasingly massive volumes of multi-modal data are being accumulated in many {real world} settings, including in health care and e-commerce. This development calls for effective…
Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration
Zhonggen Li, Xiangyu Ke, Yifan Zhu +2
Graph embeddings map graph nodes to continuous vectors and are foundational to community detection, recommendation, and many scientific applications. At billion-scale, however, exi…
Accelerating Graph Indexing for ANNS on Modern CPUs
Mengzhao Wang, Haotian Wu, Xiangyu Ke +3
In high-dimensional vector spaces, Approximate Nearest Neighbor Search (ANNS) is a key component in database and artificial intelligence infrastructures. Graph-based methods, parti…
HC-SpMM: Accelerating Sparse Matrix-Matrix Multiplication for Graphs with Hybrid GPU Cores
Zhonggen Li, Xiangyu Ke, Yifan Zhu +2
Sparse Matrix-Matrix Multiplication (SpMM) is a fundamental operation in graph computing and analytics. However, the irregularity of real-world graphs poses significant challenges…
DIMS: Distributed Index for Similarity Search in Metric Spaces
Yifan Zhu, Chengyang Luo, Tang Qian +3
Similarity search finds objects that are similar to a given query object based on a similarity metric. As the amount and variety of data continue to grow, similarity search in metr…
GTS: GPU-based Tree Index for Fast Similarity Search
Yifan Zhu, Ruiyao Ma, Baihua Zheng +3
Similarity search, the task of identifying objects most similar to a given query object under a specific metric, has gathered significant attention due to its practical application…