Author

G. de Micheli

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Preprint Oct 2026

Rosemary: Efficient and Adaptable In-Storage Acceleration for Fully Homomorphic Encryption

Fully Homomorphic Encryption (FHE) enables computation on encrypted data and is promising for privacy-preserving computing. However, FHE deployment remains constrained due to massive computational, memory, and data-movement overheads. Existing acceleration strategies often overlook the storage I/O bottleneck caused by...

Xuan Wang, Tian-Qi Zhang, G. de Micheli et al. · 0 citations

Preprint Aug 2026

Understanding Calibration and Truncation Error Propagation in Training-Free Low-Rank Compression for LLMs

This work proposes a simple, training-free methodology compatible with existing frameworks to mitigate residual errors in calibration data activations accumulate across layers during compression, causing misalignment between representations simulated at compression time and those experienced at inference.

Mohanad Odema, G. de Micheli, Dayin Gou et al. · 2 citations