2 citations · 2 across the 4 of their papers we have counts for
4 papers
Large-Scale Optimization Model Auto-Formulation: Harnessing LLM Flexibility via Structured Workflow
Kuo Liang, Yuhang Lu, Jianming Mao +7
Large-scale optimization is a key backbone of modern business decision-making. However, building these models is often labor-intensive and time-consuming. We address this by propos…
PLHF: Prompt Optimization with Few-Shot Human Feedback
Chun-Pai Yang, Kan Zheng, Shou-De Lin
Automatic prompt optimization frameworks are developed to obtain suitable prompts for large language models (LLMs) with respect to desired output quality metrics. Although existing…
NuwaTS: a Foundation Model Mending Every Incomplete Time Series
Jinguo Cheng, Chunwei Yang, Wanlin Cai +3
Time series imputation is critical for many real-world applications and has been widely studied. However, existing models often require specialized designs tailored to specific mis…
AutoML-GPT: Large Language Model for AutoML
Yun-Da Tsai, Yu-Che Tsai, Bo-Wei Huang +2
With the emerging trend of GPT models, we have established a framework called AutoML-GPT that integrates a comprehensive set of tools and libraries. This framework grants users acc…