Summary of On Instruction-finetuning Neural Machine Translation Models, by Vikas Raunak et al.
On Instruction-Finetuning Neural Machine Translation Models
by Vikas Raunak, Roman Grundkiewicz, Marcin Junczys-Dowmunt
First submitted to arxiv on: 7 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces a novel approach to Neural Machine Translation (NMT) by distilling instruction following capabilities from Large Language Models (LLMs) into smaller NMT models. This finetuning recipe enables customization of translations for specific tasks, allowing NMT models to follow multiple instructions simultaneously and compose instructions without additional training data. The authors demonstrate the effectiveness of their approach on various translation-specific tasks, including formality-controlled machine translation, multi-domain adaptation, and multi-modal translations, achieving comparable performance to LLMs like GPT-3.5-Turbo. This work has implications for faster, cheaper, and more efficient serving of customized translations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper makes it possible for machines to translate languages in a way that’s controlled by specific instructions. Imagine being able to tell a machine translator what kind of tone or style you want your translation to have! The researchers found a way to teach smaller neural machine translation models to follow these instructions, just like big language models do. This allows the smaller models to perform tasks like translating text in different styles or for specific domains. The results are impressive and could make it easier to get high-quality translations quickly. |
Keywords
» Artificial intelligence » Domain adaptation » Gpt » Multi modal » Translation
