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Spring 2023

Rezaei Sarchoghaei, Navid

There has been a renewed interest in commonsense as a stepping stone toward achieving human-level intelligence. By digesting enormous amounts of data in different forms, such as visual, lingual, and sensory, humans are able to create a world model for themselves. It is hypothesized that this...

Fall 2024

Gandhi, Deep Rajesh

It has been shown that pretrained language models exhibit biases and social stereotypes. Prior work on debiasing these language models has largely focussed on modifying embedding spaces in pretraining, which is not scalable for large models. Since pretrained models are typically fine-tuned on...

Spring 2024

von der Ohe, Spencer McIntosh

It takes skilled teachers a significant amount of time and effort to create high quality reading comprehension questions, often making it impractical to target a particular reader’s weaknesses. Recently, language models have been proposed as a tool to help teachers fill this gap, allowing these...

Fall 2024

Pathak, Shashank

The COVID-19 pandemic accelerated the development of mRNA vaccines, yet iden- tifying the optimal mRNA sequence for human use, particularly for the SARS-CoV- 2 spike protein, remains challenging. This thesis focuses on optimizing the open reading frame (ORF), a crucial mRNA component composed of...

Spring 2024

Luo, Guoqing

Text attribute transfer (TAT) is a natural language processing task that involves transforming some attributes of a given text while preserving other attributes. Recently, prompting approaches have been explored in TAT with the emergence of various pretrained language models (PLMs), where a...