Project Grant 2541273
- Federal Grant Award Summary The National Science Foundation's Division of Information and Intelligent Systems awarded $340,217 to the University of Maryland, College Park under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) on August 1, 2025, to support a five-year CAREER project extending through July 31, 2030. The project will develop innovative artificial intelligence (AI)-enabled tools leveraging large language models (LLMs) to advance language...
- Project Grant Summary: Efficient Architectures and Algorithms for Language Modeling Massachusetts Institute of Technology (MIT) received a $600,000 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The award, effective July 1, 2025, through June 30, 2030, supports a CAREER project focused on developing efficient methods for large language model (LLM)...
- Federal Grant Award Summary The University of Massachusetts received a $432,656 Project Grant from the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), effective September 1, 2025 through August 31, 2029. This collaborative research initiative addresses the misalignment between how artificial intelligence (AI) language models and humans process language, specifically focusing...
- Federal Grant Award Summary The National Science Foundation's Division of Computing and Communication Foundations awarded a CAREER grant of $357,069 to The Johns Hopkins University (dated August 15, 2026, with completion targeted for July 31, 2031) to develop interpretable, large language model (LLM)-based artificial intelligence systems that enable scientific discovery by identifying structural parallels and cross-cutting connections across scientific literature domains. The primary...
- Grant Award Summary The University of Massachusetts Amherst received a $396,112 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) effective July 1, 2026, through June 30, 2031. This CAREER award supports research focused on advancing formal software specifications as a practical foundation for AI-driven software engineering systems. The project delivers three...
- Federal Project Grant Award Summary The University of Illinois received a $350,014 project grant awarded May 15, 2025, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), administered by the National Science Foundation's Division of Information and Intelligent Systems. The grant supports a five-year CAREER project extending through April 30, 2030, focused on developing responsible language models (LMs) with rigorous uncertainty quantification guarantees....
- Federal Grant Award Summary George Mason University received a $334,731 Project Grant award from the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), effective June 15, 2025, through May 31, 2030. This CAREER award supports the development of language technologies for data-scarce languages by leveraging computational grammar books rather than relying on large datasets. The...
- 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 $546,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support research at the Pennsylvania State University (Penn State) to advance trustworthy, human-centered summarization capabilities utilizing large language models. The research aims to develop novel summarization techniques that incorporate fine-grained user preferences, address fairness and bias, and honor human knowledge. The...
- Federal Project Grant Award Summary The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded Trustees of Boston University a Project Grant of $471,529 beginning September 1, 2025, and concluding August 31, 2028, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This NSF-BSF collaborative research project delivers research and development services focused on advancing interpretability and control mechanisms for large...
Project Grant Summary The University of Massachusetts Lowell received a five-year CAREER award totaling $341,598 from the National Science Foundation's Division of Computing and Communication Foundations under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), effective July 1, 2026 through June 30, 2031. This project develops a linguistically grounded framework for robust and interpretable neural language models with applications in controlled text generation and paraphrasing. The primary deliverables include methods enabling language models to follow user-defined lexical, syntactic, and discourse constraints through instruction tuning, explicit control signals, multi-objective optimization, and iterative refinement. These capabilities will support the creation of text at appropriate reading levels for second language learners, patients accessing health information, and individuals with communication or cognitive challenges. Additionally, the project advances understanding of how language models acquire and retain linguistic patterns during training by measuring performance on annotated linguistic elements to create learning timelines. The research produces methods to remove harmful patterns from models without degrading their general text generation capabilities, thereby improving reliability and safety. Educational components include student mentoring, coursework development, freely available tools and software, and interdisciplinary workshops designed to advance artificial intelligence research and public well-being. The integrated effort aims to enhance controllability and interpretability of neural language models while supporting workforce development in responsible AI technologies.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $341.6k | 5/27/26 |