Kaixuan Ji

P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks

Xiao Liu, Kaixuan Ji, Yicheng Fu et al. · 2022 · 680 citations · Full text

P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks

Xiao Liu, Kaixuan Ji, Yicheng Fu et al. · arXiv (Cornell University) · 2021 · 262 citations · Full text

Artificial Intelligence, Llm Fine-tuning, Engineering +27

Cooperatively Improving Data Center Energy Efficiency Based on Multi-Agent Deep Reinforcement Learning

Ce Chi, Kaixuan Ji, Penglei Song et al. · Energies · 2021 · 37 citations · Full text

Artificial Intelligence, Engineering, Deep Reinforcement Learning +15

Jointly Optimizing the IT and Cooling Systems for Data Center Energy Efficiency based on Multi-Agent Deep Reinforcement Learning

Ce Chi, Kaixuan Ji, Avinab Marahatta et al. · 2020 · 24 citations

Artificial Intelligence, Huge Energy Consumption, Engineering +15

Parameter-Efficient Prompt Tuning Makes Generalized and Calibrated Neural Text Retrievers

Weng Tam, Xiao Liu, Kaixuan Ji et al. · 2023 · 12 citations · Full text

Artificial Intelligence, Llm Fine-tuning, Engineering +19