15 citations · 16 across the 2 of their papers we have counts for
2 papers
cs.CL2024★ 1 cited
MURI: High-Quality Instruction Tuning Datasets for Low-Resource Languages via Reverse Instructions
Abdullatif Köksal, Marion Thaler, Ayyoob Imani +3
Instruction tuning enhances large language models (LLMs) by aligning them with human preferences across diverse tasks. Traditional approaches to create instruction tuning datasets…
cs.CL2022★ 15 cited
Towards a Broad Coverage Named Entity Resource: A Data-Efficient Approach for Many Diverse Languages
Silvia Severini, Ayyoob Imani, Philipp Dufter +1
Parallel corpora are ideal for extracting a multilingual named entity (MNE) resource, i.e., a dataset of names translated into multiple languages. Prior work on extracting MNE data…