43 citations · 96 across the 32 of their papers we have counts for
8 papers · 1 filter
SEMA-SQL: Beyond Traditional Relational Querying with Large Language Models
Yin Lin, Tianjing Zeng, Zhongjun Ding +4
Relational databases excel at structured data analysis, but real-world queries increasingly require capabilities beyond standard SQL, such as semantically matching entities across…
Large Language Model-Enhanced Relational Operators: Taxonomy, Benchmark, and Analysis
Yunxiang Su, Tianjing Zeng, Zhongjun Ding +5
With the development of large language models (LLMs), numerous studies integrate LLMs through operator-like components to enhance relational data processing tasks, e.g., filters wi…
Learned Query Optimizer in Alibaba MaxCompute: Challenges, Analysis, and Solutions
Lianggui Weng, Dandan Liu, Wenzhuang Zhu +5
Existing learned query optimizers remain ill-suited to modern distributed, multi-tenant data warehouses due to idealized modeling assumptions and design choices. Using Alibaba's Ma…
BridgeScope: A Universal Toolkit for Bridging Large Language Models and Databases
Lianggui Weng, Dandan Liu, Rong Zhu +2
As large language models (LLMs) demonstrate increasingly powerful reasoning and orchestration capabilities, LLM-based agents are rapidly proliferating for complex data-related task…
AmbiSQL: Interactive Ambiguity Detection and Resolution for Text-to-SQL
Zhongjun Ding, Yin Lin, Tianjing Zeng +3
Text-to-SQL systems translate natural language questions into SQL queries, providing substantial value for non-expert users. While large language models (LLMs) show promising resul…
PRICE: A Pretrained Model for Cross-Database Cardinality Estimation
Tianjing Zeng, Junwei Lan, Jiahong Ma +7
Cardinality estimation (CardEst) is essential for optimizing query execution plans. Recent ML-based CardEst methods achieve high accuracy but face deployment challenges due to high…
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads (Extended)
Pengfei Li, Wenqing Wei, Rong Zhu +3
For efficient query processing, DBMS query optimizers have for decades relied on delicate cardinality estimation methods. In this work, we propose an Attention-based LEarned Cardin…
SMARTFEAT: Efficient Feature Construction through Feature-Level Foundation Model Interactions
Yin Lin, Bolin Ding, H. V. Jagadish +1
Before applying data analytics or machine learning to a data set, a vital step is usually the construction of an informative set of features from the data. In this paper, we presen…