Answers.Body: <p>I've found this article that seems to answer my question:
  <a href="https://hazelcast.com/glossary/machine-learning-inference/" rel="nofollow noreferrer">https://hazelcast.com/glossary/machine-learning-inference/</a></p>
  <p>From this, my understanding is that inference-time describes when a machine learning system is put into use following training; so basically at the time of task application.</p>
  <p>I think this would mean that the paper's authors are stating that the decomposition of sub-characters is occurring whenever the model is actively translating languages in a production environment.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-11-27T20:13:32.217Z
Answers.LastActivityDate: 2021-11-27T20:13:32.217Z
Answers.UserDisplayName: ticiarai
Body: <p>I'm reading <a href="https://aclanthology.org/2020.wat-1.21.pdf" rel="nofollow noreferrer">this paper</a> for sub-character decomposition for logographic languages and the authors mention decomposition at inference-time. They're using Transformer architecture.</p>
  <p>More specifically, the authors write:</p>
  <blockquote>
  <p>We propose a flexible inference-time sub-character decomposition procedure which targets unseen characters, and show that it aids adequacy and reduces misleading overtranslation in unseen character translation.</p>
  </blockquote>
  <p>What do inference-time and inference-only decomposition mean in this context? My best guess would be that inference-time would be at some point during the decoding process, but I'm not 100% clear on whether that's the case and, if so, when exactly.</p>
  <p>I'm going to keep digging and update if I find something helpful. In the meantime, if anyone needs more context just let me know.</p>
  
Tags: <natural-language-processing><terminology><transformer><machine-translation><inference>
Title: What does it mean to apply decomposition at inference-time in a machine translation system?
UserDisplayName: ticiarai
ThreadText: # What does it mean to apply decomposition at inference-time in a machine translation system?
  
  (Asked by: username_0 on 2021-11-23)
  
  I'm reading [this paper](https://aclanthology.org/2020.wat-1.21.pdf) for sub-character decomposition for logographic languages and the authors mention decomposition at inference-time. They're using Transformer architecture.
  
  More specifically, the authors write:
  
  > We propose a flexible inference-time sub-character decomposition procedure which targets unseen characters, and show that it aids adequacy and reduces misleading overtranslation in unseen character translation.
  
  What do inference-time and inference-only decomposition mean in this context? My best guess would be that inference-time would be at some point during the decoding process, but I'm not 100% clear on whether that's the case and, if so, when exactly.
  
  I'm going to keep digging and update if I find something helpful. In the meantime, if anyone needs more context just let me know.
  
  **Tags:** natural-language-processing, terminology, transformer, machine-translation, inference
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_0 on 2021-11-27. Score: 0 | Accepted answer
  
  I've found this article that seems to answer my question:
  <https://hazelcast.com/glossary/machine-learning-inference/>
  
  From this, my understanding is that inference-time describes when a machine learning system is put into use following training; so basically at the time of task application.
  
  I think this would mean that the paper's authors are stating that the decomposition of sub-characters is occurring whenever the model is actively translating languages in a production environment.
  
  
  ---
  
  