Project Grant 2605291
- Federal Grant Award Summary Cornell University received a $300,000 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) beginning July 1, 2025 and concluding June 30, 2028. This collaborative research initiative addresses critical evaluation gaps in Large Language Models (LLMs) by developing a comprehensive framework for assessing and improving LLM-generated...
- Federal Grant Award Summary New York University received a $763,741 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 on...
- Federal Grant Award Summary New York University received a $347,549 CAREER award from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CFDA 47.070) program, effective September 1, 2025, through August 31, 2030. This project grant supports the development of interactive language systems that critically reason about textual sources to provide high-quality, current information to users. The research...
- Federal Grant Award Summary New York University received a $420,000 Project Grant from the National Science Foundation's Division of Computer and Network Systems under the Computer and Information Science and Engineering program (CFDA 47.070) for a collaborative research initiative spanning October 1, 2025, through September 30, 2028. The project delivers comprehensive research evaluating the security landscape of machine learning (ML) and artificial intelligence (AI) enabled electronic design...
- Federal Project Grant Award Summary The National Science Foundation's Division of Information and Intelligent Systems awarded a $300,000 collaborative research project grant to the University of Wisconsin-Madison on August 1, 2025, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This three-year initiative, concluding July 31, 2028, develops algorithms, theorems, and systems to address critical limitations in large language models (LLMs) by creating...
- Federal Grant Award Summary New York University received a $209,649 CAREER award from the National Science Foundation's Division of Information and Intelligent Systems (CISE program, CFDA 47.070) effective October 1, 2025, through July 31, 2027. The project develops advanced question-answering and fact-checking systems that employ natural language reasoning to provide transparent, auditable artificial intelligence (AI) solutions. The deliverable leverages pre-trained neural network models to...
- Federal Project Grant Award Summary New York University received a $300,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070), effective October 1, 2025 through September 30, 2028. The HS-SPECTRA (Hyperspectral Standardizing and Sharing Possibilities for Urban Conditions Through Toolkits, Resources and Archiving) project will develop standardized frameworks and infrastructure for hyperspectral remote sensing...
- Federal Grant Award Summary New York University received a $333,627 Project Grant award from the National Science Foundation's Division of Computing and Communication Foundations (CFDA 47.070) effective October 1, 2025, through September 30, 2029. This collaborative research initiative will develop Probabilistic Concurrent Outcome Logic (PCOL), a new formal verification framework designed to enable rigorous reasoning about concurrent randomized programs. The primary deliverables include: (1)...
- 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...
- Federal Grant Award Summary New York University received a $600,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) effective January 1, 2026, through December 31, 2028, to develop and deploy GRISL (General-Purpose Rigorous Isolation for Science Libraries). This initiative addresses critical vulnerabilities in legacy scientific software libraries written in low-level languages such as C and C++, which are...
New York University received a $300,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) effective October 1, 2025, through July 31, 2028. This collaborative research initiative focuses on developing evaluation concepts and automated assessment technologies for Large Language Models (LLMs). The project will identify a comprehensive taxonomy of evaluation concepts to diagnose LLM failure modes—such as insufficient detail in responses—and create specialized reward models (themselves LLMs) capable of reliably scoring LLM outputs against these criteria. The deliverables include the development of automated evaluation and improvement methodologies for LLM responses, curation of training datasets demonstrating correct behavior for each evaluation concept, and iterative response improvement techniques utilizing the reward models. The project will advance LLM functionality across critical dimensions including factual accuracy, informativeness, safety, appropriate abstraction levels, format compliance, and creativity. Additionally, the project commits to open-sourcing the concept taxonomy and related technologies, thereby contributing to broader advancement of LLM assessment capabilities within the research community. This work addresses gaps in current evaluation practices by moving beyond basic quality metrics to encompass the more nuanced factors essential for effective LLM-based information systems.Federal Project Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $300.0k | 11/21/25 |