12 citations · 23 across the 5 of their papers we have counts for
5 papers
Quantum-Enhanced LLM Efficient Fine Tuning
Xiaofei Kong, Lei Li, Zhaoyun Chen +10
Low-Rank Adaptation (LoRA) enables efficient fine-tuning of pre-trained language models through low-rank matrix approximation, achieving effectiveness in many scenarios. However, i…
QPanda3: A High-Performance Software-Hardware Collaborative Framework for Large-Scale Quantum-Classical Computing Integration
Tianrui Zou, Yuan Fang, Jing Wang +8
In emerging quantum-classical integration applications, the classical time cost-especially from compilation and protocol-level communication often exceeds the execution time of qua…
Variational quantum eigensolver with linear depth problem-inspired ansatz for solving portfolio optimization in finance
Shengbin Wang, Peng Wang, Guihui Li +8
Great efforts have been dedicated in recent years to explore practical applications for noisy intermediate-scale quantum (NISQ) computers, which is a fundamental and challenging pr…
VQNet 2.0: A New Generation Machine Learning Framework that Unifies Classical and Quantum
Huanyu Bian, Zhilong Jia, Menghan Dou +13
With the rapid development of classical and quantum machine learning, a large number of machine learning frameworks have been proposed. However, existing machine learning framework…
QPanda: high-performance quantum computing framework for multiple application scenarios
Menghan Dou, Tianrui Zou, Yuan Fang +8
With the birth of Noisy Intermediate Scale Quantum (NISQ) devices and the verification of "quantum supremacy" in random number sampling and boson sampling, more and more fields hop…