14 citations · 14 across the 3 of their papers we have counts for
4 papers
Late Prompt Tuning: A Late Prompt Could Be Better Than Many Prompts
Xiangyang Liu, Tianxiang Sun, Xuanjing Huang +1
Prompt tuning is a parameter-efficient tuning (PETuning) method for utilizing pre-trained models (PTMs) that simply prepends a soft prompt to the input and only optimizes the promp…
A Simple Hash-Based Early Exiting Approach For Language Understanding and Generation
Tianxiang Sun, Xiangyang Liu, Wei Zhu +7
Early exiting allows instances to exit at different layers according to the estimation of difficulty. Previous works usually adopt heuristic metrics such as the entropy of internal…
A Survey of Transformers
Tianyang Lin, Yuxin Wang, Xiangyang Liu +1
Transformers have achieved great success in many artificial intelligence fields, such as natural language processing, computer vision, and audio processing. Therefore, it is natura…
Early Exiting with Ensemble Internal Classifiers
Tianxiang Sun, Yunhua Zhou, Xiangyang Liu +5
As a simple technique to accelerate inference of large-scale pre-trained models, early exiting has gained much attention in the NLP community. It allows samples to exit early at in…