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GeMQuAD : Generating Multilingual Question Answering Datasets from Large Language Models using Few Shot Learning
April 16, 2024, 4:51 a.m. | Amani Namboori, Shivam Mangale, Andy Rosenbaum, Saleh Soltan
cs.CL updates on arXiv.org arxiv.org
Abstract: The emergence of Large Language Models (LLMs) with capabilities like In-Context Learning (ICL) has ushered in new possibilities for data generation across various domains while minimizing the need for extensive data collection and modeling techniques. Researchers have explored ways to use this generated synthetic data to optimize smaller student models for reduced deployment costs and lower latency in downstream tasks. However, ICL-generated data often suffers from low quality as the task specificity is limited with …
abstract arxiv capabilities collection context cs.ai cs.cl data data collection datasets domains emergence in-context learning language language models large language large language models llms modeling multilingual question question answering researchers type
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