Project Grant 2449280
- 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 Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CFDA #47.070) program seeks to develop responsible language models (LMs) with rigorous guarantees. The $350,014 project, with a performance period from May 15, 2025 to April 30, 2030, will be conducted by the University of Illinois. The project aims to enhance the reliability of LMs, which have significantly advanced deep learning but often result in errors in real-world...
- 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 federal Project Grant award, titled "CAREER: TOWARD IMPROVING SCALABILITY FOR EFFECTIVE HEALTH LLMS," is funded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070). The $348,227 award, effective September 1, 2025 through August 31, 2030, supports research to improve the effectiveness and scalability of large language models (LLMs) for healthcare applications. The key objectives are to develop evaluation...
- The National Science Foundation (NSF) awarded a $800,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Illinois Urbana-Champaign. The 3-year grant, effective September 1, 2024, focuses on enhancing the safety of large language models (LLMs) used in high-stakes applications. The project aims to develop quantifiable safety measures and algorithms to detect and mitigate unsafe behaviors in LLMs, such as providing false or...
- This $250,000 Project Grant award from the National Science Foundation's (NSF) Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) will fund a study on the ethical and financial trade-offs of machine learning (ML) training methods used to develop large language models (LLMs) like ChatGPT. The study, conducted by Georgia Tech Research Corp, will: 1) Identify current practices among researchers for training LLMs using large datasets; 2) Examine the trade-offs of different data...
- This $200,000 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). The grant supports a collaborative research project led by Virginia Polytechnic Institute & State University (Virginia Tech) to develop new algorithms, theorems, and systems for reliable large language models (LLMs) and open-world foundation models (OWFMs). The key focus is to create an expandable...
- This $300,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will support research to develop improved evaluation techniques for large language models (LLMs). The University of Texas at Austin will lead this collaborative research project focused on identifying "evaluation concepts" to assess factors like factuality, informativeness, and alignment with user needs in LLM responses. The project aims to...
- This $275,000 federal Project Grant award from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) supports Relai, Inc.'s development of innovative methodologies to enhance the reliability of large language models (LLMs). The key products and services to be delivered include: Methodologies to inspect and mitigate jailbreaking issues in LLMs, where adversarial prompts can circumvent model alignment. Methodologies to inspect and...
- 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 award from the National Science Foundation's Technology, Innovation, and Partnerships (CFDA 47.084) program provides funding of $320,000 to Lehigh University to establish an open-source ecosystem named OpenTrustLLM. The project aims to develop a collaborative framework for evaluating and enhancing the trustworthiness of large language models (LLMs), which are increasingly used in critical sectors like healthcare, finance, and national security. The key objectives include refactoring the current trustworthiness evaluation platform, developing continuous integration workflows, establishing a governing committee, and expanding the user and developer community. The project will integrate multiple evaluation tools to cover critical trustworthiness dimensions such as robustness, privacy, and safety. By promoting confidence in AI technologies, this effort is expected to advance national health, economic growth, and benefit the broader public through more dependable AI applications. The project duration is from August 15, 2025, to July 31, 2026.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $20.0k | 9/4/25 | ||
| Not listed | $300.0k | 8/4/25 |