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20242026
most citedAutomate Strategy Finding with LLM in Quant Investment

3 citations · 5 across the 8 of their papers we have counts for

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cs.DB2026

Cache-Aware I/O Cost Modeling for Disk-Based Learned Indexes

Zhanwei Shi, Meng Zhang, Guangyi Zhang +5

Learned indexes have shown attractive space-time trade-offs in main-memory settings, yet a principled I/O cost model for their disk-resident deployments is still missing, which is…

cs.DB2025

CARPO: Leveraging Listwise Learning-to-Rank for Context-Aware Query Plan Optimization

Wenrui Zhou, Qiyu Liu, Jingshu Peng +2

Efficient data processing is increasingly vital, with query optimizers playing a fundamental role in translating SQL queries into optimal execution plans. Traditional cost-based op…

cs.DB2025

Piecewise Linear Approximation in Learned Index Structures: Theoretical and Empirical Analysis

Jiayong Qin, Xianyu Zhu, Qiyu Liu +7

A growing trend in the database and system communities is to augment conventional index structures, such as B+-trees, with machine learning (ML) models. Among these, error-bounded…

cs.DB2024★ 1 cited

Learned Data Compression: Challenges and Opportunities for the Future

Qiyu Liu, Siyuan Han, Jianwei Liao +4

Compressing integer keys is a fundamental operation among multiple communities, such as database management (DB), information retrieval (IR), and high-performance computing (HPC).…

cs.DB2024

Why Are Learned Indexes So Effective but Sometimes Ineffective?

Qiyu Liu, Siyuan Han, Yanlin Qi +4

Learned indexes have attracted significant research interest due to their ability to offer better space-time trade-offs compared to traditional B+-tree variants. Among various lear…