13 citations · 13 across the 4 of their papers we have counts for
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MoCE: Adaptive Mixture of Contextualization Experts for Byte-based Neural Machine Translation
Langlin Huang, Mengyu Bu, Yang Feng
Byte-based machine translation systems have shown significant potential in massively multilingual settings. Unicode encoding, which maps each character to specific byte(s), elimina…
Integrating Multi-scale Contextualized Information for Byte-based Neural Machine Translation
Langlin Huang, Yang Feng
Subword tokenization is a common method for vocabulary building in Neural Machine Translation (NMT) models. However, increasingly complex tasks have revealed its disadvantages. Fir…
Enhancing Neural Machine Translation with Semantic Units
Langlin Huang, Shuhao Gu, Zhuocheng Zhang +1
Conventional neural machine translation (NMT) models typically use subwords and words as the basic units for model input and comprehension. However, complete words and phrases comp…
BayLing: Bridging Cross-lingual Alignment and Instruction Following through Interactive Translation for Large Language Models
Shaolei Zhang, Qingkai Fang, Zhuocheng Zhang +8
Large language models (LLMs) have demonstrated remarkable prowess in language understanding and generation. Advancing from foundation LLMs to instructionfollowing LLMs, instruction…