This three-year $800,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to advance understanding of large language models through mathematical and conceptual analysis. The Trustees of Princeton University will receive funding to develop simplified generative text models, analyze how language models are trained on such generated texts, examine why learned models can perform downstream tasks, and design new adaptation methods with...
The National Science Foundation Division of Information and Intelligent Systems awarded a $500,000 Project Grant to Stanford University from October 1, 2021 to September 30, 2024 under the Computer and Information Science and Engineering program (CFDA 47.070). The grant funds research to develop new tools for studying structural and inductive bias in natural language processing models. The Computer and Information Science and Engineering program supports investigator-initiated research and...
The National Science Foundation's Division of Information and Intelligent Systems awarded $454,115 under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to Stanford University. The three-year Project Grant will support research to accelerate machine learning through the development of automated methods to clean data, reduce feature dimensionality, and recommend machine learning models using low-dimensional latent vectors. Principal Investigator will...
The National Science Foundation has awarded a $299,990 Project Grant to Columbia University to develop a prototype system using large language models to assist in the review process for releasing government records. The project aims to determine the additional data and training required to achieve acceptable levels of accuracy in using large language models to identify information that is already in the public domain, in order to streamline the document review process. The iterative system...
The National Science Foundation (NSF) awarded a $225,000 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to The Leland Stanford Junior University. The 3-year grant, effective July 1, 2024, aims to gain a deeper theoretical understanding of the statistical properties of neural networks, which have revolutionized science and engineering. Key research directions include studying the distinguishing features of deep neural networks compared to classical statistical...
This $400,000 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The objective of the award is to leverage and evaluate large language models (LLMs) as "tools for thought" that can support creative, open-ended, and collaborative work across various applications such as scientific writing, text analysis, and design ideation. The key products and services to be developed and...
This $400,000 Project Grant award from the National Science Foundation (NSF) STEM Education program (CFDA 47.076) to the University of California, San Diego (UCSD) aims to redesign an introductory computer science (CS1) course to teach programming with the aid of large language model (LLM) AI assistants. The key goals are to: 1) Redesign the CS1 course to emphasize skills like code reading, testing, and problem decomposition rather than just syntax and writing code from scratch; 2) Study how...
The National Science Foundation (NSF) awarded a $199,994 Project Grant through the STEM Education (CFDA 47.076) program to The Leland Stanford Junior University to explore how high school youth, particularly those from historically marginalized communities, interact with and learn about generative AI and machine learning tools. Over a one-year period, the researchers will pilot classroom and extracurricular activities, collect quantitative and qualitative data, and analyze findings to develop...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award of $799,999 to the University of Washington provides funding for a 4-year collaborative research project focused on developing tools and methods to leverage large language models (LLMs) in support of divergent, convergent, and cooperative work. The key objectives of the project are to: 1) Develop design guidance and workflows for building more reliable and...
This $499,999 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support collaborative research to investigate the theoretical foundations of compositional learning in large language models (LLMs) based on transformer architectures. The research aims to advance the understanding of how LLMs, such as GPT-4, LLAMA 2, and CLAUDE 3, can decompose complex tasks into simpler intermediate steps to...