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Sheng-Feng Yu

2 accepted papers

2026

SkipCat: Rank-Maximized Low-Rank Compression of Large Language Models via Shared Projection and Block Skipping

AAAI 2026technical

Large language models (LLM) have achieved remarkable performance across a wide range of tasks. However, their substantial parameter sizes pose significant challenges for deployment on edge devices with limited computational and memory resources. Low-rank compression is a promising approach to addres

Cited by 0SourcePDFScholar
2025

Boost Self-Supervised Dataset Distillation via Parameterization, Predefined Augmentation, and Approximation

ICLR 2025poster

Although larger datasets are crucial for training large deep models, the rapid growth of dataset size has brought a significant challenge in terms of considerable training costs, which even results in prohibitive computational expenses. Dataset Distillation becomes a popular technique recently to re…

Cited by 0SourcePDFScholar