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Physical Sciences and Mathematics Commons

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Artificial Intelligence and Robotics

University of Massachusetts Amherst

2023

Large language models

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Effective And Efficient Transfer Learning In The Era Of Large Language Models, Tu Vu Nov 2023

Effective And Efficient Transfer Learning In The Era Of Large Language Models, Tu Vu

Doctoral Dissertations

Substantial progress has been made in the field of natural language processing (NLP) due to the advent of large language models (LLMs)—deep neural networks with millions or billions of parameters pre-trained on large amounts of unlabeled data. However, these models have common weaknesses, including degenerate performance in data-scarce scenarios, and substantial computational resource requirements. This thesis aims to develop methods to address these limitations for improved applicability and performance of LLMs in resource-constrained settings with limited data and/or computational resources. To address the need for labeled data in data-scarce scenarios, I present two methods, in Chapter 2 and Chapter 3, …