5 papers · 1 filter
Limited Linguistic Diversity in Embodied AI Datasets
Selma Wanna, Agnes Luhtaru, Jonathan Salfity +4
Language plays a critical role in Vision-Language-Action (VLA) models, yet the linguistic characteristics of the datasets used to train and evaluate these systems remain poorly doc…
Teaching Llama a New Language Through Cross-Lingual Knowledge Transfer
Hele-Andra Kuulmets, Taido Purason, Agnes Luhtaru +1
This paper explores cost-efficient methods to adapt pretrained Large Language Models (LLMs) to new lower-resource languages, with a specific focus on Estonian. Leveraging the Llama…
To Err Is Human, but Llamas Can Learn It Too
Agnes Luhtaru, Taido Purason, Martin Vainikko +2
This study explores enhancing grammatical error correction (GEC) through artificial error generation (AEG) using language models (LMs). Specifically, we fine-tune Llama 2-based LMs…
Autocorrect for Estonian texts: final report from project EKTB25
Agnes Luhtaru, Martin Vainikko, Krista Liin +4
The project was funded in 2021-2023 by the National Programme of Estonian Language Technology. Its main aim was to develop spelling and grammar correction tools for the Estonian la…
Grammatical Error Correction and Style Transfer via Zero-shot Monolingual Translation
Elizaveta Korotkova, Agnes Luhtaru, Maksym Del +3
Both grammatical error correction and text style transfer can be viewed as monolingual sequence-to-sequence transformation tasks, but the scarcity of directly annotated data for ei…