Project Grant 2211955
- The National Science Foundation awarded $1,200,000 under the Computer and Information Science and Engineering program (CFDA 47.070) to Northeastern University for a four-year project grant beginning July 2022. The grant supports research to advance neural summarization models for specialized domains with limited training data, where factually accurate summaries are critical. Researchers will evaluate state-of-the-art models fine-tuned for domains like medicine and characterize their factual...
- 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...
- This Project Grant from the National Science Foundation's Computer and Information Science and Engineering program totaling $169,989 supports research at Portland State University from April 1, 2023 to March 31, 2025 toward developing new algorithms and datasets for generating socially diverse multi-document text summarization of user-generated social data. The goal is to improve automatic summarization models to better reflect a broad spectrum of diverse perspectives found in socially rich data...
- Summary Analytics Inc. received a $276,000 Small Business Innovation Research Phase I Project Grant from the National Science Foundation to translate its universal text summarization system technology over the period of August 1, 2021 to July 31, 2022. Funded through the NSF's Engineering program (CFDA #47.041), which seeks to improve quality of life and economic strength through engineering innovation and education, the project supports Summary Analytics in further developing its...
- This $174,995 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to understand and optimize the role of human intelligence in data integration and discovery pipelines, especially in the context of emerging large language models (LLMs) like ChatGPT. The project will investigate fundamental questions about human involvement in these data processes, uncover relevant human biases, and...
- Federal Project Grant Summary The National Science Foundation's Division of Information and Intelligent Systems awarded a $300,000 project grant to the University of Virginia on August 1, 2025, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This three-year research initiative, concluding July 31, 2028, develops advanced methodologies to optimize knowledge utilization in large language models (LLMs) to improve scientific research ideation. The project...
- Federal Grant Award Summary Carnegie Mellon University received a $508,043 project grant awarded on August 1, 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 five-year project, concluding July 31, 2030, will deliver foundational research and algorithmic tools focused on developing robust machine learning (ML) systems capable of withstanding...
- This $550,000 Project Grant award from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program supports the development of generative artificial intelligence (AI)-powered products that enable humans to interact and converse with books and other documents. The key products being developed include: Technology to represent the informational content of books and document discussions as a knowledge graph, which will then be used to ground large...
- 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 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...
- Federal Project Grant Award Summary Carnegie Mellon University received a $600,000 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), awarded June 1, 2025, with completion targeted for May 31, 2028. This award funds fundamental research investigating computational mechanisms of visual cortical recurrent circuits in the early brain, with the objective of...
This Project Grant from the National Science Foundation's Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), provides $1,167,492 to Carnegie Mellon University to support research into expert-in-the-loop neural summarization for specialized domains from July 2022 to June 2026. Specifically, the university will critically evaluate and extend the capabilities of modern pre-trained neural summarization models for use in domains like medicine where training data is limited and factual accuracy is paramount. Researchers will characterize model outputs with respect to factual accuracy when fine-tuned for low-resource domains. They will also develop techniques for interactive expert supervision via active learning and highlight-based annotation, as well as novel pre-training objectives. Transparent and controllable latent variable summarization architectures will be designed to allow domain experts to verify summaries by inspecting influential input segments. The goal is to leverage automated summarization while ensuring expert trust through technical innovations enabling oversight and debugging.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $583.7k | 6/27/22 |