Towards Unified Multi-Domain Machine Translation With Mixture of Domain Experts-Reference-Cited by-同舟云学术

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Towards Unified Multi-Domain Machine Translation With Mixture of Domain Experts

Published:2023 Issue: Volume:31 Page:3488-3498
ISSN:2329-9290
Container-title:IEEE/ACM Transactions on Audio, Speech, and Language Processing
language:
Short-container-title:IEEE/ACM Trans. Audio Speech Lang. Process.

Author:

Lu Jinliang¹^ORCID,Zhang Jiajun¹^ORCID

Affiliation:

1. Institute of Automation, Chinese Academy of Sciences, Beijing, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Acoustics and Ultrasonics,Computer Science (miscellaneous),Computational Mathematics

Link

http://xplorestaging.ieee.org/ielx7/6570655/9970249/10255669.pdf?arnumber=10255669

Reference38 articles.

1. Exploring Discriminative Word-Level Domain Contexts for Multi-Domain Neural Machine Translation

2. An Empirical Comparison of Domain Adaptation Methods for Neural Machine Translation

3. Multi-Domain Neural Machine Translation with Word-Level Domain Context Discrimination

4. Stanford neural machine translation systems for spoken language domains;luong;Proc 12th Int Workshop Spoken Lang Transl Eval Campaign,0

5. Learning multiple visual domains with residual adapters;rebuffi;Proc Adv Neural Inf Process Syst,0

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