Multilingual Neural Machine Translation With the Right Amount of Sharing

no code implementations • EAMT 2022 • Taido Purason, Andre Tättar

Large multilingual Transformer-based machine translation models have had a pivotal role in making translation systems available for hundreds of languages with good zero-shot translation performance.

Machine Translation NMT +1

MTee: Open Machine Translation Platform for Estonian Government

no code implementations • EAMT 2022 • Toms Bergmanis, Marcis Pinnis, Roberts Rozis, Jānis Šlapiņš, Valters Šics, Berta Bernāne, Guntars Pužulis, Endijs Titomers, Andre Tättar, Taido Purason, Hele-Andra Kuulmets, Agnes Luhtaru, Liisa Rätsep, Maali Tars, Annika Laumets-Tättar, Mark Fishel

We present the MTee project - a research initiative funded via an Estonian public procurement to develop machine translation technology that is open-source and free of charge.

Document Translation Grammatical Error Correction +2

Teaching Llama a New Language Through Cross-Lingual Knowledge Transfer

no code implementations • 5 Apr 2024 • Hele-Andra Kuulmets, Taido Purason, Agnes Luhtaru, Mark Fishel

This paper explores cost-efficient methods to adapt pretrained Large Language Models (LLMs) to new lower-resource languages, with a specific focus on Estonian.

Instruction Following Llama +1

To Err Is Human, but Llamas Can Learn It Too

no code implementations • 8 Mar 2024 • Agnes Luhtaru, Taido Purason, Martin Vainikko, Maksym Del, Mark Fishel

This study explores enhancing grammatical error correction (GEC) through artificial error generation (AEG) using language models (LMs).

GPT-3.5 GPT-4 +2