15 citations · 48 across the 7 of their papers we have counts for
8 papers
A Roadmap for Big Model
Sha Yuan, Hanyu Zhao, Shuai Zhao +97
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm. Researchers have achieved various outcomes in the c…
Integrating Vectorized Lexical Constraints for Neural Machine Translation
Shuo Wang, Zhixing Tan, Yang Liu
Lexically constrained neural machine translation (NMT), which controls the generation of NMT models with pre-specified constraints, is important in many practical scenarios. Due to…
Language Models are Good Translators
Shuo Wang, Zhaopeng Tu, Zhixing Tan +3
Recent years have witnessed the rapid advance in neural machine translation (NMT), the core of which lies in the encoder-decoder architecture. Inspired by the recent progress of la…
CPM-2: Large-scale Cost-effective Pre-trained Language Models
Zhengyan Zhang, Yuxian Gu, Xu Han +16
In recent years, the size of pre-trained language models (PLMs) has grown by leaps and bounds. However, efficiency issues of these large-scale PLMs limit their utilization in real-…
On the Language Coverage Bias for Neural Machine Translation
Shuo Wang, Zhaopeng Tu, Zhixing Tan +3
Language coverage bias, which indicates the content-dependent differences between sentence pairs originating from the source and target languages, is important for neural machine t…
Neural Machine Translation: A Review of Methods, Resources, and Tools
Zhixing Tan, Shuo Wang, Zonghan Yang +4
Machine translation (MT) is an important sub-field of natural language processing that aims to translate natural languages using computers. In recent years, end-to-end neural machi…