collaborators

6 papers

cs.AI2026

QuantumQA: Enhancing Scientific Reasoning via Physics-Consistent Dataset and Verification-Aware Reinforcement Learning

Songxin Qu, Tai-Ping Sun, Yun-Jie Wang +8

Large language models (LLMs) show strong capabilities in general reasoning but typically lack reliability in scientific domains like quantum mechanics, which demand strict adherenc…

cs.LG2026

Quantum-Inspired Fine-Tuning for Few-Shot AIGC Detection via Phase-Structured Reparameterization

Kaiyang Xing, Han Fang, Zhaoyun Chen +4

Recent studies show that quantum neural networks (QNNs) generalize well in few-shot regimes. To extend this advantage to large-scale tasks, we propose Q-LoRA, a quantum-enhanced fi…

quant-ph2026

Q-Tag: Watermarking Quantum Circuit Generative Models

Yang Yang, Yuzhu Long, Han Fang +4

Quantum cloud platforms have become the most widely adopted and mainstream approach for accessing quantum computing resources, due to the scarcity and operational complexity of qua…

quant-ph2025

Quantum Computational Insurance and Actuarial Science

Huan-Yu Liu, Xi-Ning Zhuang, Chao Wang +7

In recent years, quantum computation has been rapidly advancing, driving a technological revolution with significant potential across various sectors, particularly in finance. Desp…

cs.PL2025

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…

quant-ph2025

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…