NSF award 2555319 · University of Tulsa

Collaborative Research: SaTC 2.0: RES: Achieving Reliable, Interpretable, and Efficient At-scale Machine Unlearning on Generative AI Models

Final report due

28 January 2030

in 1,198 days · The award ends on 30 September 2029.

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award ending 2029-09-30 · Research.gov
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Final report due28 Jan 2030in 1198 days
award ending 2029-09-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Jan 2030in 1198 days
award ending 2029-09-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Jan 2030in 1198 days
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PAPPG 24-1: “financially closed out 120 days after their expiration date”

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NSF lists this award's end date as 30 September 2029.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 January 2030.

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Award card

Award number: 2555319
Period of support: 1 Oct 2026 – 30 Sep 2029
Amount: $500,787
Awardee: University of Tulsa, Tulsa, OK
Program: Secure &Trustworthy Cyberspace
Directorate: CSE

Abstract

Generative models like GPT and Stable Diffusion have significantly advanced the capabilities of artificial intelligence. Despite their impressive performance, these models can generate undesirable outputs, including private user data, copyrighted material, and inappropriate content. In response, machine unlearning approaches enable the removal of data influences and harmful concepts from pretrained models to comply…

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