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Barah Fazili

2 accepted papers

2024

Boosting Zero-Shot Crosslingual Performance using LLM-Based Augmentations with Effective Data Selection

ACL 2024findings

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…

2022

Aligning Multilingual Embeddings for Improved Code-switched Natural Language Understanding

COLING 2022main

Multilingual pretrained models, while effective on monolingual data, need additional training to work well with code-switched text. In this work, we present a novel idea of training multilingual models with alignment objectives using parallel text so as to explicitly align word representations with…