Project Grant 2504264
- This Project Grant award, titled "ADVANCING LARGE LANGUAGE MODEL UNLEARNING: FOUNDATIONS AND APPLICATIONS", is funded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The $268,000 award will be executed by Michigan State University from October 1, 2025 to September 30, 2029. The project aims to establish a comprehensive foundation for "unlearning" in large language models (LLMs), enabling the targeted...
- The National Science Foundation (NSF) awarded a $266,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to The Leland Stanford Junior University (Stanford University) to advance research in Large Language Model (LLM) unlearning. The project aims to develop new algorithmic frameworks, model interpretability approaches, and data management techniques to enable the targeted removal of harmful content and behaviors from pretrained LLMs without...
- The National Science Foundation (NSF) awarded a $500,000 Project Grant under the Engineering program (CFDA 47.041) to Wayne State University, located in Detroit, Michigan. The goal of this 5-year research project, which commenced on October 1, 2025, is to investigate fundamental limits and algorithmic principles for trustworthy sequential decision-making in artificial intelligence and machine learning (AI/ML) systems, particularly those powered by reinforcement learning. The research focuses...
- This National Science Foundation (NSF) Project Grant award 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) system. The $471,529 award to Trustees of Boston University aims to develop methods for identifying and characterizing multi-dimensional and continuous internal representations within LLMs, rather than just simple binary concepts. This work...
- This $220,000 federal Project Grant award, provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CFDA #47.070) program, will support a collaborative research project led by Duke University to investigate and develop new defenses against prompt injection attacks on large language models (LLMs). The research aims to deepen the understanding of such cyber-attack threats and establish foundational security principles for the rapidly growing ecosystem...
- The National Science Foundation (NSF) awarded a $600,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of South Carolina. The grant, with a period of performance from October 1, 2024 to September 30, 2027, focuses on enhancing security and mitigating harm in AI-generated vision language models. Key technical objectives include: 1) Developing a prompting framework for detecting harmful content provenance in AI-generated vision...
- This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) provides $100,000 to The Pennsylvania State University to develop an open, community-driven evaluation infrastructure for assessing the safety risks of large language models (LLMs). The project aims to advance AI safety research, foster public awareness, and strengthen workforce training in responsible AI practices. Key objectives include...
- 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 $348,227 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to improve the scalability and effectiveness of large language models (LLMs) used in healthcare applications. The key objectives are to develop an evaluation framework to address issues like factual and faithfulness hallucinations in LLM outputs, and to introduce innovative reinforcement learning methods to better align LLM...
- This Project Grant award of $599,721.00 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) Federal Grant Program will establish a secure, easy-to-use ecosystem to enable safe and trustworthy use of multi-modal large language models (MLLMs) in food science research. The project will: (i) profile MLLMs on their effectiveness, robustness, efficiency, and security, (ii) recommend the best MLLM candidates for scientific tasks, and (iii) embed...
This Project Grant award from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) provides $266,000.00 to Wayne State University to advance research on large language model (LLM) unlearning. The project aims to develop new algorithmic frameworks, model interpretability approaches, and data handling techniques to enable the targeted removal of harmful data influences and behaviors from pretrained LLMs without compromising their overall performance. Key objectives include promoting trustworthy AI, strengthening data privacy, and enabling contextually-adaptive systems aligned with social norms. The project also includes educational and outreach activities such as curriculum development, workshops, and open-source software. The award period runs from October 1, 2025 to September 30, 2029.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $266.0k | 7/31/25 |