3 papers
cs.LG2026
Artificial Entanglement in the Fine-Tuning of Large Language Models
Min Chen, Zihan Wang, Canyu Chen +3
Large language models (LLMs) can be adapted to new tasks using parameter-efficient fine-tuning (PEFT) methods that modify only a small number of trainable parameters, often through…
quant-ph2025
An Analytic Theory of Quantum Imaginary Time Evolution
Min Chen, Bingzhi Zhang, Quntao Zhuang +1
Quantum imaginary time evolution (QITE) algorithm is one of the most promising variational quantum algorithms (VQAs), bridging the current era of Noisy Intermediate-Scale Quantum d…
quant-ph2025
GroverGPT: A Large Language Model with 8 Billion Parameters for Quantum Searching
Haoran Wang, Pingzhi Li, Min Chen +3
Quantum computing is an exciting non-Von Neumann paradigm, offering provable speedups over classical computing for specific problems. However, the practical limits of classical sim…