6 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.CL2024★ 6 cited
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Haoran Li, Qingxiu Dong, Zhengyang Tang +17
We introduce Generalized Instruction Tuning (called GLAN), a general and scalable method for instruction tuning of Large Language Models (LLMs). Unlike prior work that relies on se…
cs.CL2023★ 1 cited
Tuna: Instruction Tuning using Feedback from Large Language Models
Haoran Li, Yiran Liu, Xingxing Zhang +2
Instruction tuning of open-source large language models (LLMs) like LLaMA, using direct outputs from more powerful LLMs such as Instruct-GPT and GPT-4, has proven to be a cost-effe…
cs.CL2021★ 1 cited
Mixed Cross Entropy Loss for Neural Machine Translation
Haoran Li, Wei Lu
In neural machine translation, cross entropy (CE) is the standard loss function in two training methods of auto-regressive models, i.e., teacher forcing and scheduled sampling. In…