Summary of Aya Dataset: An Open-access Collection For Multilingual Instruction Tuning, by Shivalika Singh et al.

Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning

by Shivalika Singh, Freddie Vargus, Daniel Dsouza, Börje F. Karlsson, Abinaya Mahendiran, Wei-Yin Ko, Herumb Shandilya, Jay Patel, Deividas Mataciunas, Laura OMahony, Mike Zhang, Ramith Hettiarachchi, Joseph Wilson, Marina Machado, Luisa Souza Moura, Dominik Krzemiński, Hakimeh Fadaei, Irem Ergün, Ifeoma Okoh, Aisha Alaagib, Oshan Mudannayake, Zaid Alyafeai, Vu Minh Chien, Sebastian Ruder, Surya Guthikonda, Emad A. Alghamdi, Sebastian Gehrmann, Niklas Muennighoff, Max Bartolo, Julia Kreutzer, Ahmet Üstün, Marzieh Fadaee, Sara Hooker

First submitted to arxiv on: 9 Feb 2024

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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 addresses a critical issue in natural language processing (NLP), where most datasets are in English, limiting the ability of large language models (LLMs) to respond to instructions in other languages. To bridge this gap, the authors construct a human-curated instruction-following dataset spanning 65 languages, leveraging fluent speakers from around the world to collect natural instances of instructions and completions. This effort results in the largest multilingual collection to date, with over 513 million instances through templating and translating existing datasets across 114 languages. The authors also develop and open-source the Aya Annotation Platform, the Aya Dataset, the Aya Collection, and the Aya Evaluation Suite, providing valuable resources for future research collaborations.
Low	GrooveSquid.com (original content)	Low Difficulty Summary Imagine trying to teach a computer to follow instructions in many different languages. That’s what this paper is all about. Right now, most computers can only understand English instructions, which limits their ability to help people who speak other languages. The authors of this paper worked with people from around the world to create a huge collection of instructions and answers in 65 different languages. This will make it easier for computers to understand and respond to instructions in many languages, which is important for things like language translation and helping people communicate.