4 papers
Think in Latent, Explain in Language: Self-Explainable Latent Reasoning
Dayuan Zhao, Shengcao Cao, Yu-Xiong Wang +1
Latent reasoning has emerged as a powerful alternative to text-based Chain-of-Thought (CoT), offering significant gains in computational efficiency by compressing verbose reasoning…
Spectral Complex Autoencoder Pruning: A Fidelity-Guided Criterion for Extreme Structured Channel Compression
Wei Liu, Xing Deng, Haijian Shao +1
We propose Spectral Complex Autoencoder Pruning (SCAP), a reconstruction-based criterion that measures functional redundancy at the level of individual output channels. For each co…
One-Shot Structured Pruning of Quantum Neural Networks via -Group Engineering and Quantum Geometric Metrics
Haijian Shao, Wei Liu, Xing Deng +1
Quantum neural networks (QNNs) suffer from severe gate-level redundancy, which hinders their deployment on noisy intermediate-scale quantum (NISQ) devices. In this work, we propose…
LiePrune: Lie Group and Quantum Geometric Dual Representation for One-Shot Structured Pruning of Quantum Neural Networks
Haijian Shao, Bowen Yang, Wei Liu +2
Quantum neural networks (QNNs) and parameterized quantum circuits (PQCs) are key building blocks for near-term quantum machine learning. However, their scalability is constrained b…