Project Grant 2515156
- This $300,000 Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) federal grant program (CFDA 47.070) to Cornell University. The grant aims to develop new evaluation concepts and technologies for assessing and improving large language models (LLMs) used in text summarization and generation applications. The project will create a concept taxonomy and customized reward models to evaluate LLM responses across...
- This $471,529 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to expand the understanding of large language models (LLMs), a type of artificial intelligence (AI). The project at the Trustees of Boston University aims to move beyond identifying simple, binary concepts within LLMs and instead develop methods to discover and characterize more sophisticated, multi-dimensional...
- 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...
- This Project Grant award from the National Science Foundation (NSF) Mathematical and Physical Sciences Program (CFDA 47.049) provides $210,000 to Cornell University to conduct research on analyzing the structural and algorithmic characteristics of high-dimensional probability models encountered in statistical inference and physics. The research objectives are to characterize the computational relevance of phase transitions in spin systems and neural network models, devise efficient algorithms...
- The National Science Foundation awarded a $400,000 Project Grant to Stanford University under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The three-year award will support research and education activities to develop conceptual and mathematical understanding of large language models. Specifically, the university will conduct research analyzing simplified generative text models and language models trained on such data to gain insights into their inner...
- This Project Grant award of $300,000 from the National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program supports a study at Georgetown University to develop an evaluation methodology for measuring the impacts of implementing large language model (LLM)-based tools to assist human experts working in federal, state, and local government programs. The project will compare the performance of LLM-only, human-only, and human-LLM hybrid responses across key metrics...
- This federal Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program provides $594,753 to Cornell University to develop new methods for controlling generative artificial intelligence (AI) systems that produce text and images. The research aims to improve the reliability and safety of these AI technologies, especially in sensitive applications like healthcare, customer service, and education. The project will...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program provides $333,333.00 to Cornell University for a 3-year collaborative research project. The project aims to develop a novel "neurosymbolic programming framework" called Foundation Model Programming to generate symbolically interpretable scientific hypotheses from high-dimensional observational data. This approach seeks to leverage the contextual...
- This $175,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will fund research to develop new statistical and computational methods to enhance the reliability of data analysis in modern, large-scale datasets, particularly in the era of AI. The key areas of focus include: (1) analyzing the robustness of manifold and deep learning algorithms for high-dimensional, noisy, and nonlinear data; (2) developing statistical theory...
- 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...
This federal Project Grant award from the National Science Foundation (NSF) Mathematical and Physical Sciences program (CFDA 47.049) provides $250,000 to Cornell University to develop new statistical models and methods for analyzing data from large language models (LLMs). The project "SOFTMAX MIXTURE ENSEMBLES FOR LEVERAGING LLM OUTPUT" aims to create computationally efficient techniques for summarizing and interpreting the complex, high-dimensional outputs of current LLMs, which contain billions of parameters and are difficult to directly use in subsequent analyses. The research will produce robust, interpretable methods based on softmax mixture ensemble models to identify meaningful latent topics within diverse document corpora. This work is expected to provide critical insights into similarities and differences between human-generated and AI-generated text by Aug 15, 2025, with a planned completion date of Jul 31, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $250.0k | 8/14/25 |