Summary of From Llm to Nmt: Advancing Low-resource Machine Translation with Claude, by Maxim Enis and Mark Hopkins
From LLM to NMT: Advancing Low-Resource Machine Translation with Claude
by Maxim Enis, Mark Hopkins
First submitted to arxiv on: 22 Apr 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 demonstrates that Claude 3 Opus, a large language model (LLM) released by Anthropic, outperforms other LLMs in machine translation tasks. Despite finding evidence of data contamination with Claude on the FLORES-200 dataset, new benchmarks show its effectiveness for low-resource machine translation into English. The study highlights Claude’s remarkable resource efficiency, showcasing how it can produce high-quality translations using limited language pair resources. Additionally, the paper shows that advancements in LLM translation can be compressed into traditional neural machine translation (NMT) models. By generating synthetic data with Claude and applying knowledge distillation, the authors achieve state-of-the-art results in Yoruba-English translation, surpassing strong baselines like NLLB-54B and Google Translate. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at a new language model called Claude 3 Opus. They tested it to see how good it is at translating text from one language to another. The results show that Claude is really good at this, even when working with languages that don’t have much data available. The authors also found a way to use Claude to make traditional translation models better. This means we can get more accurate translations without needing as many resources. |
Keywords
» Artificial intelligence » Claude » Knowledge distillation » Language model » Large language model » Synthetic data » Translation
