|
Translation and Large Language Models| title | Translation and Large Language Models |
|---|
| start_date | 2024/03/15 |
|---|
| schedule | 11h |
|---|
| online | no |
|---|
| location_info | Salle C434 & en visio |
|---|
| summary | What is the future of translation research in the era of large language models? Brown et al. in 2020 showed that prompting GPT3 with a few examples of translation could result in translations which were higher quality than SOTA supervised models at the time (into English and only for French, German). Until this point, research on machine translation had been central to the field of natural language processing, often attracting the most submissions in annual NLP conferences and leading to many breakthroughs in the field. Since then, there has been enormous interest in models which can perform a wide variety of tasks and interest in translation as a separate sub-field has somewhat diminished. However, translation remains a compelling and widely used technology. So what is the promise of LLMs for translation and how should we best use them? What opportunities do LLMs unlock and what challenges remain? How can the field of translation still contribute to NLP? I will touch on some of my own research but I focus on these broader questions. |
|---|
| responsibles | Bawden |
|---|
Workflow history| from state (1) | to state | comment | date |
|---|
| submitted | published | | 2024/03/14 11:57 UTC |
| |
|