Findings of the Second Workshop on Neural Machine Translation and Generation
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Abstract (arXiv)
This document describes the findings of the Second Workshop on Neural Machine Translation and Generation, held in concert with the annual conference of the Association for Computational Linguistics (ACL 2018). First, we summarize the research trends of papers presented in the proceedings, and note that there is particular interest in linguistic structure, domain adaptation, data augmentation, handling inadequate resources, and analysis of models. Second, we describe the results of the workshop's shared task on efficient neural machine translation, where participants were tasked with creating MT systems that are both accurate and efficient.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Jun 2018.
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Citing papers per year: 2021: 3; 2022: 1; 2023: 1.
5 papers.
- 2021Neural Machine Translation for Low-Resource Languages: A Surveycited by 109
- 2021An Efficient Transformer Decoder with Compressed Sub-layerscited by 10
- 2023Efficiency Pentathlon: A Standardized Arena for Efficiency Evaluationcited by 7
- 2021MOROCCO: Model Resource Comparison Frameworkcited by 0
- 2022CUNI Non-Autoregressive System for the WMT 22 Efficient Translation Shared Taskcited by 0
- 2023Efficiency Pentathlon: A Standardized Arena for Efficiency Evaluation19 Jul 2023
- 2022CUNI Non-Autoregressive System for the WMT 22 Efficient Translation Shared Task1 Dec 2022
- 2021Neural Machine Translation for Low-Resource Languages: A Survey29 Jun 2021
- 2021MOROCCO: Model Resource Comparison Framework29 Apr 2021
- 2021An Efficient Transformer Decoder with Compressed Sub-layers3 Jan 2021