4 papers
Why Not Transform Chat Large Language Models to Non-English?
Xiang Geng, Ming Zhu, Jiahuan Li +14
The scarcity of non-English data limits the development of non-English large language models (LLMs). Transforming English-centric LLMs to non-English has been identified as an effe…
Investigating Numerical Translation with Large Language Models
Wei Tang, Jiawei Yu, Yuang Li +5
The inaccurate translation of numbers can lead to significant security issues, ranging from financial setbacks to medical inaccuracies. While large language models (LLMs) have made…
DeMPT: Decoding-enhanced Multi-phase Prompt Tuning for Making LLMs Be Better Context-aware Translators
Xinglin Lyu, Junhui Li, Yanqing Zhao +4
Generally, the decoder-only large language models (LLMs) are adapted to context-aware neural machine translation (NMT) in a concatenating way, where LLMs take the concatenation of…
Using Large Language Model for End-to-End Chinese ASR and NER
Yuang Li, Jiawei Yu, Min Zhang +6
Mapping speech tokens to the same feature space as text tokens has become the paradigm for the integration of speech modality into decoder-only large language models (LLMs). An alt…