13 citations · 13 across the 5 of their papers we have counts for
6 papers · 1 filter
EstLLM: Enhancing Estonian Capabilities in Multilingual LLMs via Continued Pretraining and Post-Training
Aleksei Dorkin, Taido Purason, Emil Kalbaliyev +7
Large language models (LLMs) are predominantly trained on English-centric data, resulting in uneven performance for smaller languages. We study whether continued pretraining (CPT)…
Estonian WinoGrande Dataset: Comparative Analysis of LLM Performance on Human and Machine Translation
Marii Ojastu, Hele-Andra Kuulmets, Aleksei Dorkin +3
In this paper, we present a localized and culturally adapted Estonian translation of the test set from the widely used commonsense reasoning benchmark, WinoGrande. We detail the tr…
Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures
Tyler A. Chang, Catherine Arnett, Abdelrahman Sadallah +377
To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we pre…
LLMs for Extremely Low-Resource Finno-Ugric Languages
Taido Purason, Hele-Andra Kuulmets, Mark Fishel
The advancement of large language models (LLMs) has predominantly focused on high-resource languages, leaving low-resource languages, such as those in the Finno-Ugric family, signi…
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…
Kratt: Developing an Automatic Subject Indexing Tool for The National Library of Estonia
Marit Asula, Jane Makke, Linda Freienthal +2
Manual subject indexing in libraries is a time-consuming and costly process and the quality of the assigned subjects is affected by the cataloguer's knowledge on the specific topic…