mlsanityData to 7 Oct 2026

Compact Personalized Models for Neural Machine Translation

arXiv 1811.01990 ↗First posted 5 Nov 2018cs.CLcited by 19

Not on the map. Why?

Abstract (arXiv)

We propose and compare methods for gradient-based domain adaptation of self-attentive neural machine translation models. We demonstrate that a large proportion of model parameters can be frozen during adaptation with minimal or no reduction in translation quality by encouraging structured sparsity in the set of offset tensors during learning via group lasso regularization. We evaluate this technique for both batch and incremental adaptation across multiple data sets and language pairs. Our system architecture - combining a state-of-the-art self-attentive model with compact domain adaptation - provides high quality personalized machine translation that is both space and time efficient.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Nov 2018.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 4; 2022: 5; 2023: 7; 2024: 3.

19 papers.

Sort:

By area:

  1. 2023LaMP: When Large Language Models Meet Personalizationcited by 425
  2. 2023Tool Learning with Foundation Modelscited by 302
  3. 2024Optimization Methods for Personalizing Large Language Models through Retrieval Augmentationcited by 98
  4. 2023Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedbackcited by 86
  5. 2023Adaptive Machine Translation with Large Language Modelscited by 58
  6. 2021Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A Surveycited by 46
  7. 2024Exploring Safety-Utility Trade-Offs in Personalized Language Modelscited by 26
  8. 2021Learning Kernel-Smoothed Machine Translation with Retrieved Examplescited by 25
  9. 2022On the Domain Adaptation and Generalization of Pretrained Language Models: A Surveycited by 22
  10. 2022Chunk-based Nearest Neighbor Machine Translationcited by 21
  11. 2021Pruning-then-Expanding Model for Domain Adaptation of Neural Machine Translationcited by 15
  12. 2022Non-Parametric Domain Adaptation for End-to-End Speech Translationcited by 12
7 more
  1. 2023Simple and Scalable Nearest Neighbor Machine Translationcited by 12
  2. 2024Adapters for Altering LLM Vocabularies: What Languages Benefit the Most?cited by 9
  3. 2022Sockeye 3: Fast Neural Machine Translation with PyTorchcited by 3
  4. 2022PePe: Personalized Post-editing Model utilizing User-generated Post-editscited by 1
  5. 2021More Parameters? No Thanks!cited by 0
  6. 2023Bridging the Domain Gaps in Context Representations for k-Nearest Neighbor Neural Machine Translationcited by 0
  7. 2023Epi-Curriculum: Episodic Curriculum Learning for Low-Resource Domain Adaptation in Neural Machine Translationcited by 0