3 citations · 3 across the 2 of their papers we have counts for
4 papers
From Blind Search to Memory-Aware Evolution: Efficient DBMS Tuning via Collaborative Diagnosis and Utility-Aware Retrieval
Zhaoyan Hong, Yishen Sun, Xinyi Zhang +7
Modern DBMSs expose multiple configurable components (e.g., knobs, query hints, and indexes) that jointly determine query performance. Multi-component tuning is challenging due to…
Why Database Manuals Are Not Enough: Efficient and Reliable Configuration Tuning for DBMSs via Code-Driven LLM Agents
Xinyi Zhang, Tiantian Chen, Zhentao Han +9
Modern database management systems (DBMSs) expose hundreds of configuration knobs that critically influence performance. Existing automated tuning methods either adopt a data-drive…
Text-to-Layout: A Generative Workflow for Drafting Architectural Floor Plans Using LLMs
Jayakrishna Duggempudi, Lu Gao, Ahmed Senouci +2
This paper presents the development of an AI-powered workflow that uses Large Language Models (LLMs) to assist in drafting schematic architectural floor plans from natural language…
Large Language Model-Driven Code Compliance Checking in Building Information Modeling
Soumya Madireddy, Lu Gao, Zia Din +4
This research addresses the time-consuming and error-prone nature of manual code compliance checking in Building Information Modeling (BIM) by introducing a Large Language Model (L…