Project Grant 2537827

Award Date 9/1/25
Completion Date 8/31/27
Dollars Obligated $300K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Urbana, IL 61801, USA
Similar Awards
This $300,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to improve the evaluation and functionality of large language models (LLMs). The University of Texas at Austin will lead this 3-year collaborative research project to identify a taxonomy of "evaluation concepts" for assessing LLM responses and develop technology to automatically evaluate and improve LLM performance based on...
This Project Grant award, valued at $347,549, was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program. The award supports research by New York University (NYU) to develop interactive language systems that can critically reason about textual sources to provide high-quality, up-to-date information. The key focus areas include: (1) expanding the definition of document relevancy to incorporate...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, with a total funding of $175,000, aims to develop more reliable and trustworthy question-answering AI systems by integrating large language models with structured knowledge graphs. The research at the University of California, Merced will create novel computational methods to ensure AI outputs are grounded in verified knowledge, reducing errors and improving...
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...
This $174,995 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to understand and optimize the role of human intelligence in data integration and discovery pipelines, especially in the context of emerging large language models (LLMs) like ChatGPT. The project will investigate fundamental questions about human involvement in these data processes, uncover relevant human biases, and...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) provides $381,276 to the University of California, San Diego (UCSD) to develop next-generation machine reasoning capabilities centered on "world models". The key objectives are to: (1) create new inference algorithms that induce internal world models within large language models to enable strategic planning and deliberate...
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 Project Grant award from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) to the Rector & Visitors of the University of Virginia (UVA) provides $300,000 to develop approaches that optimize the utilization of external and internal knowledge in large language models (LLMs) to foster research ideation. The key activities include: Developing an adversary-based reasoning approach to effectively harness the parametric knowledge within LLMs to...
This $763,741 project grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program aims to better align how human and artificial intelligence (AI) models process language. The researchers at New York University will explore techniques to modify AI architectures, such as adopting semantic training objectives and leveraging causal intervention methods, to bring them more in line with how humans derive meaning from sentences and handle...
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 $300,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of a structure-guided reasoning approach for multi-hop, complex reasoning using large language models (LLMs). The project aims to create a framework integrating three key tasks: retrieving task-focused data and information, structuring the retrieved data and knowledge, and reasoning on the structured data and knowledge. It will result in new algorithms for information retrieval, data and knowledge structuring, and structure-guided reasoning, which will be broadly applicable across data science fields. The project will leverage public scientific texts as datasets and plans to disseminate shared data and benchmarks to the broader data science and AI communities. No sub-awards are planned for this award, which has an ultimate completion date of August 31, 2027.

Generated 8/5/25, 2:54 AM