7 citations · 8 across the 5 of their papers we have counts for
5 papers
NLoRA: Nyström-Initiated Low-Rank Adaptation for Large Language Models
Chenlu Guo, Yuan Wu, Yi Chang
Parameter-efficient fine-tuning (PEFT) is essential for adapting large language models (LLMs), with low-rank adaptation (LoRA) being the most popular approach. However, LoRA suffer…
Asymmetric Co-Training for Source-Free Few-Shot Domain Adaptation
Gengxu Li, Yuan Wu
Source-free unsupervised domain adaptation (SFUDA) has gained significant attention as an alternative to traditional unsupervised domain adaptation (UDA), which relies on the const…
Interpretable Droplet Digital PCR Assay for Trustworthy Molecular Diagnostics
Yuanyuan Wei, Yucheng Wu, Fuyang Qu +5
Accurate molecular quantification is essential for advancing research and diagnostics in fields such as infectious diseases, cancer biology, and genetic disorders. Droplet digital…
An Effective and Resilient Backdoor Attack Framework against Deep Neural Networks and Vision Transformers
Xueluan Gong, Bowei Tian, Meng Xue +3
Recent studies have revealed the vulnerability of Deep Neural Network (DNN) models to backdoor attacks. However, existing backdoor attacks arbitrarily set the trigger mask or use a…
A Survey on Data Augmentation in Large Model Era
Yue Zhou, Chenlu Guo, Xu Wang +2
Large models, encompassing large language and diffusion models, have shown exceptional promise in approximating human-level intelligence, garnering significant interest from both a…