Domain Adaptive Inference for Neural Machine Translation
Not on the map. Why?
Abstract (arXiv)
We investigate adaptive ensemble weighting for Neural Machine Translation, addressing the case of improving performance on a new and potentially unknown domain without sacrificing performance on the original domain. We adapt sequentially across two Spanish-English and three English-German tasks, comparing unregularized fine-tuning, L2 and Elastic Weight Consolidation. We then report a novel scheme for adaptive NMT ensemble decoding by extending Bayesian Interpolation with source information, and show strong improvements across test domains without access to the domain label.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Jun 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 3; 2022: 2; 2023: 0; 2024: 3; 2025: 0; 2026: 2.
10 papers.
- 2024Learning to Decode Collaboratively with Multiple Language Modelscited by 61
- 2021Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A Surveycited by 46
- 2021Pruning-then-Expanding Model for Domain Adaptation of Neural Machine Translationcited by 15
- 2022Continual Knowledge Distillation for Neural Machine Translationcited by 4
- 2024Instruction-tuned Large Language Models for Machine Translation in the Medical Domaincited by 4
- 2022Improving Robustness of Retrieval Augmented Translation via Shuffling of Suggestionscited by 2
- 2021Improving Scheduled Sampling with Elastic Weight Consolidation for Neural Machine Translationcited by 1
- 2024F-MALLOC: Feed-forward Memory Allocation for Continual Learning in Neural Machine Translationcited by 1
- 2026Preventing Error Propagation in Multi-Agent AI through Runtime Monitoringcited by 1
- 2026BERAG: Bayesian Ensemble Retrieval-Augmented Generation for Knowledge-based Visual Question Answeringcited by 0
- 2026Preventing Error Propagation in Multi-Agent AI through Runtime Monitoring27 Jun 2026
- 2026BERAG: Bayesian Ensemble Retrieval-Augmented Generation for Knowledge-based Visual Question Answering24 Apr 2026
- 2024Instruction-tuned Large Language Models for Machine Translation in the Medical Domain29 Aug 2024
- 2024F-MALLOC: Feed-forward Memory Allocation for Continual Learning in Neural Machine Translation7 Apr 2024
- 2024Learning to Decode Collaboratively with Multiple Language Models6 Mar 2024
- 2022Continual Knowledge Distillation for Neural Machine Translation18 Dec 2022
- 2022Improving Robustness of Retrieval Augmented Translation via Shuffling of Suggestions11 Oct 2022
- 2021Improving Scheduled Sampling with Elastic Weight Consolidation for Neural Machine Translation13 Sep 2021
- 2021Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A Survey14 Apr 2021
- 2021Pruning-then-Expanding Model for Domain Adaptation of Neural Machine Translation25 Mar 2021