REU Site: Recent Advances in Natural Language Processing

The objective of this project is to expose motivated undergraduates who aspire to pursue advanced careers in Computer Science, in particular in Artificial Intelligence and Machine Learning (AI-ML), to active research experience early in their careers. This project will develop a summer Research Experience for Undergraduates (REU) site at the University of Colorado, Colorado Springs, to engage ten participants per year from around the country in cutting-edge research on topics such as the use and security of Large Language Models, and the use of the new paradigm of Quantum Computing to better solve problems in Natural Language Processing. The students will write software to solve interesting and timely problems, write papers for publication, and will be exposed to procedures for applying for graduate school. The proposal will also focus on training future computer scientists from institutions with limited research opportunities. The research experience will encourage these students to be productive researchers in academic and non-academic environments during their future careers. The participating students will be introduced to the latest advances such as Deep Learning, Large Language Models, and Quantum Computing via focused lectures, discussion of latest publications, and personalized readings. In particular, the students will learn about latest innovations in Deep Learning, including Transformer-inspired architectures, such as the Bidirectional Encoder Representations from Transformers (BERT) and the Generative Pre-Trained Transformers (GPT) series, that have ushered in a recent period of sustained improved results to many problems that have been the focus of research for years. The students will perform hands-on research on novel problems, conduct experiments using Transformer-based Deep Learning architectures and Quantum Computing methods, and communicate their results through written papers and presentations. Example projects will involve controlling generation of large language models; defending language models against attacks; and the use of Quantum Computing in solving tasks such as part-of-speech tagging and named entity recognition. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.