← all papers · overview

Boosting Zero-shot Crosslingual Performance Using Llm-based Augmentations With Effective Data Selection

Abstract

Large language models (LLMs) are very proficient text generators. We leverage this capability of LLMs to generate task-specific data via zero-shot prompting and promote cross-lingual transfer for low-resource target languages. Given task-specific data in a source language and a teacher model trained on this data, we propose using this teacher to label LLM generations and employ a set of simple dat

Related papers

Ranked by semantic similarity — how closely each paper's abstract matches this one (100% = near-identical topic).