Project Grant 2531126
- This Project Grant award of $175,000 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program advances trustworthy artificial intelligence (AI) by developing methods to integrate large language models with structured knowledge graphs. The research, conducted by the University of California, Merced, aims to create more reliable and accurate AI-powered question answering systems. The key technical advances include synergistic knowledge...
- This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) provides $400,000.00 to the University of California, Berkeley (UC Berkeley) to conduct research on understanding, visualizing, and attributing multimodal generative models - large-scale AI models that generate both text and images. The research aims to develop new systematic frameworks for analyzing the internal mechanisms and...
- This $500,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE, CFDA 47.070) program supports research by the Regents of the University of California at Riverside to study security vulnerabilities in machine learning (ML) models. The project aims to understand how malicious actors could exploit unused parameters in trained ML models to install additional, potentially harmful functionality without detection. The research...
- 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...
- 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 $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...
- 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 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) provides $300,000 to the Regents of the University of California at Riverside to conduct research on adapting foundation models for multimodal sequential decision-making. The project aims to develop novel techniques and methods to leverage foundation models, which are complex neural networks trained on large datasets, to improve the performance of...
- This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) program aims to develop software frameworks that can efficiently serve and deploy machine learning models for a variety of AI-powered applications. The $600,000 award, spanning from October 2024 to September 2027, tasks the prime awardee, Georgia Tech Research Corporation, with creating agile mechanisms and policies to serve a family of AI models across...
- This $599,411 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of a "Trustworthy Toolbox for Double-Correct Predictive Modeling in Sciences." The project aims to create advanced artificial intelligence (AI) and machine learning (ML) models that can make accurate predictions while also providing transparent, scientifically-grounded rationales for their outputs. This...
This Project Grant award, titled "ENABLING A SAFE AND DIRECTIVE MULTI-MODAL FOUNDATION MODEL ECOSYSTEM FOR FOOD SCIENCE RESEARCH", is funded by the National Science Foundation (NSF) through its Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The $599,721 award, granted to the University of California, Davis (UC Davis), aims to establish a secure, easy-to-use ecosystem that (i) profiles multi-modal large language models on their effectiveness, robustness, efficiency, and security, (ii) recommends the best models for scientific tasks, and (iii) embeds automated safeguards to ensure trustworthy and reproducible AI-powered discoveries. This project will advance the reliability and usability of foundational AI models for the scientific ecosystem, addressing key challenges in model selection, threat identification, and safeguards, with a focus on food science research applications such as microbial detection and micro-nutrient formulation. The 3-year project will run from September 1, 2025 to August 31, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $599.7k | 7/28/25 |