This $719,494 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to the University of California, San Diego (UCSD). The grant supports research on compositional semantics-guided program synthesis, which aims to develop more scalable and general synthesis algorithms to enable the creation of larger software systems. The key products or services to be delivered include novel...
This $334,731 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program aims to leverage grammar books to develop language technologies for data-scarce languages. The project will (1) build datasets to explore the meta-linguistic capabilities of large language models, (2) explore building large language models for new languages using grammars, (3) make theoretical connections to learning paradigms and model...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) Project Grant award of $112,818 to the University of California, Santa Barbara (UCSB) aims to improve the understanding, correction, and adaptation of large language models (LLMs) from a knowledge-oriented perspective. The project will focus on four key research thrusts: 1) understanding how external knowledge interacts with LLM behavior, 2) developing methods to enable LLMs to...
The University of California, San Diego (UCSD) was awarded a 5-year, $165,000 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The goal of this project is to develop algorithms, software, and systems that can automatically generate high-quality labeled data to mitigate the lack of labeled training data in specialized domains such as healthcare, legislation, and environmental sciences. The proposed approaches...
This $300,000 federal Project Grant award from the National Science Foundation's (NSF) STEM Education (CFDA 47.076) program aims to develop a course that teaches computer science students how to work with and comprehend large code bases. The project, awarded to the University of California, San Diego (UC San Diego), is designed to address the "academia-industry gap" where new computer science graduates are often underprepared for contributing to large, existing software code bases in...
The National Science Foundation (NSF) awarded a Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of California, Davis (UC Davis) for the project "EAGER: PROOF-CARRYING CODE COMPLETIONS." The $300,000 award, with a project period running from February 15, 2024 to July 31, 2025, will support the development of tools, techniques, and empirical results for using large language models to generate trustworthy code completions...
The National Science Foundation awarded a $400,000 Project Grant to Stanford University under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The three-year award will support research and education activities to develop conceptual and mathematical understanding of large language models. Specifically, the university will conduct research analyzing simplified generative text models and language models trained on such data to gain insights into their inner...
This $100,000 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) program aims to develop a holistic benchmarking infrastructure for evaluating large language models used in software engineering. The key activities include: Conducting surveys and interviews with the software engineering and machine learning research communities to gather requirements and understand barriers in evaluating large language models for code....
This three-year National Science Foundation Project Grant of $1,048,850 will fund the development of new techniques for translating English language specifications into formal specifications accepted by software quality tools. Drexel University will receive the funding under the Computer and Information Science and Engineering program (CFDA 47.070) to pursue approaches connecting natural language software behavior descriptions to semi-formal specifications used in property-based testing...
This $174,999 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support a research project at the University of Central Missouri. The project aims to develop a unified, large language model (LLM)-empowered framework to systematically address software performance challenges. Key objectives include automating performance testing, issue localization, and optimization. The research will integrate...