7 citations · 17 across the 20 of their papers we have counts for
4 papers · 1 filter
Is Large Language Model Good at Database Knob Tuning? A Comprehensive Experimental Evaluation
Yiyan Li, Haoyang Li, Zhao Pu +6
Knob tuning plays a crucial role in optimizing databases by adjusting knobs to enhance database performance. However, traditional tuning methods often follow a Try-Collect-Adjust a…
FacLens: Transferable Probe for Foreseeing Non-Factuality in Fact-Seeking Question Answering of Large Language Models
Yanling Wang, Haoyang Li, Hao Zou +4
Despite advancements in large language models (LLMs), non-factual responses still persist in fact-seeking question answering. Unlike extensive studies on post-hoc detection of thes…
E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model
Xinmei Huang, Haoyang Li, Jing Zhang +7
Database knob tuning is a significant challenge for database administrators, as it involves tuning a large number of configuration knobs with continuous or discrete values to achie…
CodeS: Towards Building Open-source Language Models for Text-to-SQL
Haoyang Li, Jing Zhang, Hanbing Liu +7
Language models have shown promising performance on the task of translating natural language questions into SQL queries (Text-to-SQL). However, most of the state-of-the-art (SOTA)…