mlsanityData to 14 Oct 2026

Sockeye 3: Fast Neural Machine Translation with PyTorch

arXiv 2207.05851 ↗First posted 12 Jul 2022cs.CLcited by 3

Not on the map. Why?

Abstract (arXiv)

Sockeye 3 is the latest version of the Sockeye toolkit for Neural Machine Translation (NMT). Now based on PyTorch, Sockeye 3 provides faster model implementations and more advanced features with a further streamlined codebase. This enables broader experimentation with faster iteration, efficient training of stronger and faster models, and the flexibility to move new ideas quickly from research to production. When running comparable models, Sockeye 3 is up to 126% faster than other PyTorch implementations on GPUs and up to 292% faster on CPUs. Sockeye 3 is open source software released under the Apache 2.0 license.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 23 of its 33 references that are in the map. First posted on arXiv 12 Jul 2022.

Builds on

23 of 33 references.

References · 23

  1. 2017Attention Is All You Needcited by 60,361
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  3. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  4. 2015Neural Machine Translation of Rare Words with Subword Unitscited by 2,918
  5. 2018SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processingcited by 1,989
  6. 2019fairseq: A Fast, Extensible Toolkit for Sequence Modelingcited by 1,488
  7. 2020Beyond English-Centric Multilingual Machine Translationcited by 561
  8. 2016Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translationcited by 469
  9. 2017OpenNMT: Open-source Toolkit for Neural Machine Translationcited by 251
  10. 2018Scaling Neural Machine Translationcited by 204
  11. 2015MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systemscited by 195
  12. 2019CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEBcited by 177
11 more
  1. 2016Linguistic Input Features Improve Neural Machine Translationcited by 38
  2. 2019Controlling the Output Length of Neural Machine Translationcited by 36
  3. 2022CoCoA-MT: A Dataset and Benchmark for Contrastive Controlled MT with Application to Formalitycited by 24
  4. 2018Marian: Cost-effective High-Quality Neural Machine Translation in C++cited by 22
  5. 2019JParaCrawl: A Large Scale Web-Based English-Japanese Parallel Corpuscited by 21
  6. 2018Compact Personalized Models for Neural Machine Translationcited by 19
  7. 2021Isometric MT: Neural Machine Translation for Automatic Dubbingcited by 18
  8. 2020The Sockeye 2 Neural Machine Translation Toolkit at AMTA 2020cited by 16
  9. 2022The Devil is in the Details: On the Pitfalls of Vocabulary Selection in Neural Machine Translationcited by 3
  10. 2017Sharp Models on Dull Hardware: Fast and Accurate Neural Machine Translation Decoding on the CPUcited by 2
  11. 2021Faithful Target Attribute Prediction in Neural Machine Translationcited by 2

Built on by

Cited by year

Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 1.

3 papers.