2 code implementations • 9 Aug 2023 • Wenhao Zhu, Yunzhe Lv, Qingxiu Dong, Fei Yuan, Jingjing Xu, ShuJian Huang, Lingpeng Kong, Jiajun Chen, Lei LI
We start from targeting individual languages by performing cross-lingual instruction-tuning (CoIT) on LLaMA, i. e. tuning it with translation task data and cross-lingual general task data to obtain cross-lingual models (x-LLaMAs), and formulate underlying scaling laws to investigate the advantages of using scalable translation data.
1 code implementation • 27 Feb 2023 • Wenhao Zhu, Qianfeng Zhao, Yunzhe Lv, ShuJian Huang, Siheng Zhao, Sizhe Liu, Jiajun Chen
Augmenting the base neural model with a token-level symbolic datastore is a novel generation paradigm and has achieved promising results in machine translation (MT).
1 code implementation • 8 Nov 2022 • Wenhao Zhu, ShuJian Huang, Yunzhe Lv, Xin Zheng, Jiajun Chen
kNN-MT presents a new paradigm for domain adaptation by building an external datastore, which usually saves all target language token occurrences in the parallel corpus.