Project Grant R01EB038873
- This federal Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program provides $763,741 to New York University (NYU) to conduct collaborative research on how to better align artificial intelligence (AI) language models, like ChatGPT, with human language processing. The goal is to understand why AI models do not exhibit the same challenges as humans in processing temporary semantic ambiguity in language, and to...
- This Project Grant award from the National Science Foundation's Division of Information and Intelligent Systems (CFDA 47.070 - Computer and Information Science and Engineering) supports research into probing the inner workings of artificial intelligence (AI) systems and comparing them to human cognition during speech recognition. The $50,000 award to the University of Southern California (USC) will fund the development of novel mathematical models and experimental methods to examine how AI...
- This federal Project Grant award of $432,656 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program supports collaborative research to better align how artificial intelligence (AI) language models and humans process language. The primary goal is to understand why AI models, such as ChatGPT, do not process language in the same way as humans, particularly around handling temporary semantic ambiguity. The researchers will benchmark the AI models...
- 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...
- This $234,610 Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports collaborative research at Colgate University to study how the brain uses visual and linguistic information to achieve specific goals. The research aims to advance theories of human cognition and develop more adaptive, human-aligned artificial intelligence (AI) systems. Key project activities include training deep neural networks to predict...
- This $240,000 federal Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) is supporting research at Yale University to develop new computational frameworks that combine large language models with neural operator learning techniques. The goal is to improve the ability to model and analyze spatiotemporal phenomena in biomedical research, such as tracking cellular and brain processes over time and...
- This Project Grant award from the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program provides $378,352 to Barnard College to conduct research on how the brain uses visual and linguistic information to achieve specific goals. The project aims to understand the cognitive processes underlying goal-directed perception, using a combination of methods from visual AI, language AI, neuroscience, and cognitive science. Key activities include training deep neural...
- This federal Project Grant award for $653,230.00, provided by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) under the Discovery and Applied Research for Technological Innovations to Improve Human Health program (CFDA 93.286), supports the development of MED-SCALLOP - a novel neurosymbolic AI methodology and software tool. The goal is to create inherently explainable AI/ML models for clinical decision support in healthcare, which can effectively integrate deep neural...
- This federal Project Grant award of $679,182, provided by the National Institute on Deafness and Other Communication Disorders (NIDCD) under the Research Related to Deafness and Communication Disorders program (CFDA 93.173), supports the development of new computational models that leverage multimodal neuroimaging and demographic data to predict post-stroke aphasia and language recovery. The key objective is to build an interpretable, modular platform that can identify effective treatments and...
- The federal Project Grant award titled "COLLABORATIVE RESEARCH: PREDICTIVE PROCESSING IN NATURALISTIC LANGUAGE COMPREHENSION THROUGH EEG AND COMPUTATIONAL MODELING" is funded by the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program. The $280,336 award to the Regents of the University of Michigan will support a 3-year research project studying brain signals and computational models to investigate how bilingual individuals comprehend language...
The federal Project Grant award of $221,224 was provided by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) under the Discovery and Applied Research for Technological Innovations to Improve Human Health program (CFDA 93.286). The award will fund research to develop AI language models with working memory constraints that better approximate those of humans, and conduct experiments with human participants to determine the extent to which these models can explain neural data on language processing. The project aims to develop neuroscientifically plausible AI language models and advance the understanding of how the brain processes language. The award was made to New York University and has an ultimate completion date of July 31, 2029.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $221.2k | 8/15/25 |