34 citations · 67 across the 5 of their papers we have counts for
5 papers
SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression
Xin Wang, Yu Zheng, Zhongwei Wan +1
The advancements in Large Language Models (LLMs) have been hindered by their substantial sizes, which necessitates LLM compression methods for practical deployment. Singular Value…
Efficient Large Language Models: A Survey
Zhongwei Wan, Xin Wang, Che Liu +9
Large Language Models (LLMs) have demonstrated remarkable capabilities in important tasks such as natural language understanding and language generation, and thus have the potentia…
Deep AutoAugment
Yu Zheng, Zhi Zhang, Shen Yan +1
While recent automated data augmentation methods lead to state-of-the-art results, their design spaces and the derived data augmentation strategies still incorporate strong human p…
Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?
Shen Yan, Yu Zheng, Wei Ao +2
Existing Neural Architecture Search (NAS) methods either encode neural architectures using discrete encodings that do not scale well, or adopt supervised learning-based methods to…
HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking
Shen Yan, Biyi Fang, Faen Zhang +4
The use of automatic methods, often referred to as Neural Architecture Search (NAS), in designing neural network architectures has recently drawn considerable attention. In this wo…