10 citations · 10 across the 4 of their papers we have counts for
Showing cs.CLShow all
3 papers · 1 filter
cs.CL2023
Exploring the impact of low-rank adaptation on the performance, efficiency, and regularization of RLHF
Simeng Sun, Dhawal Gupta, Mohit Iyyer
During the last stage of RLHF, a large language model is aligned to human intents via PPO training, a process that generally requires large-scale computational resources. In this t…
cs.CL2023★ 10 cited
How Does In-Context Learning Help Prompt Tuning?
Simeng Sun, Yang Liu, Dan Iter +2
Fine-tuning large language models is becoming ever more impractical due to their rapidly-growing scale. This motivates the use of parameter-efficient adaptation methods such as pro…
cs.CL2023
Efficiently Upgrading Multilingual Machine Translation Models to Support More Languages
Simeng Sun, Maha Elbayad, Anna Sun +1
With multilingual machine translation (MMT) models continuing to grow in size and number of supported languages, it is natural to reuse and upgrade existing models to save computat…