7 citations · 14 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 7 cited
Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing
Dujian Ding, Ankur Mallick, Chi Wang +5
Large language models (LLMs) excel in most NLP tasks but also require expensive cloud servers for deployment due to their size, while smaller models that can be deployed on lower c…
cs.DB2024
Budget-aware Query Tuning: An AutoML Perspective
Wentao Wu, Chi Wang
Modern database systems rely on cost-based query optimizers to come up with good execution plans for input queries. Such query optimizers rely on cost models to estimate the costs…
cs.SE2023★ 7 cited
EcoAssistant: Using LLM Assistant More Affordably and Accurately
Jieyu Zhang, Ranjay Krishna, Ahmed H. Awadallah +1
Today, users ask Large language models (LLMs) as assistants to answer queries that require external knowledge; they ask about the weather in a specific city, about stock prices, an…