← Search

Xiuqing Lv

2 accepted papers

2023

LightFormer: Light-weight Transformer Using SVD-based Weight Transfer and Parameter Sharing

ACL 2023findings

Transformer has become an important technique for natural language processing tasks with great success. However, it usually requires huge storage space and computational cost, making it difficult to be deployed on resource-constrained edge devices. To compress and accelerate Transformer, we propose…

2022

Hypoformer: Hybrid Decomposition Transformer for Edge-friendly Neural Machine Translation

EMNLP 2022main

Transformer has been demonstrated effective in Neural Machine Translation (NMT). However, it is memory-consuming and time-consuming in edge devices, resulting in some difficulties for real-time feedback. To compress and accelerate Transformer, we propose a Hybrid Tensor-Train (HTT) decomposition, wh…

Cited by 13SourcePDFScholar