Summary of Multilingual Instruction Tuning with Just a Pinch Of Multilinguality, by Uri Shaham et al.
Multilingual Instruction Tuning With Just a Pinch of Multilinguality
by Uri Shaham, Jonathan Herzig, Roee Aharoni, Idan Szpektor, Reut Tsarfaty, Matan Eyal
First submitted to arxiv on: 3 Jan 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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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 investigates how instruction-tuning large language models (LLMs) in multiple languages affects their ability to follow instructions across different languages. The study finds that even monolingual tuning can transfer some instruction-following capabilities to other languages, and that integrating only 40 multilingual examples into an English training set can significantly improve multilingual instruction-following. Furthermore, the results show that models trained on multilingual mixtures exhibit comparable or superior performance in multiple languages compared to monolingually trained models. The study also finds that diversifying the instruction-tuning set with just a few additional languages can lead to improved cross-lingual generalization. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how teaching large language models to follow instructions in many different languages helps them understand instructions in those same languages. The research shows that even when training on only one language, some of the instruction-following skills can be transferred to other languages. It also finds that adding just a few examples of instructions from other languages can make the model much better at following instructions in all the languages it was trained on. Overall, the study suggests that teaching models to follow instructions in many languages is a good way to help them understand instructions in those same languages. |
Keywords
* Artificial intelligence * Generalization * Instruction tuning
