NSF award 2541273 · University of Massachusetts Lowell

CAREER: From Learning to Forgetting: Linguistic Complexity, Learning Dynamics, and Robustness in Neural Language Models

Final report due

28 October 2031

in 1,836 days · The award ends on 30 June 2031.

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Decide about an extension2 Mar 2031in 1596 days
award ending 2031-06-30 · Research.gov
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Extension request16 May 2031in 1671 days
award ending 2031-06-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Jun 2031in 1706 days
award ending 2031-06-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Oct 2031in 1836 days
award ending 2031-06-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Oct 2031in 1836 days
award ending 2031-06-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Oct 2031in 1836 days
award ending 2031-06-30 · Research.gov
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 June 2031.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 October 2031.

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Award card

Award number: 2541273
Period of support: 1 Jul 2026 – 30 Jun 2031
Amount: $487,997
Awardee: University of Massachusetts Lowell, Lowell, MA
Program: Info Integration & Informatics
Directorate: CSE

Abstract

Artificial intelligence systems that generate text now influence how people search for information, learn new skills, obtain health advice, and communicate online. Yet these systems can behave in ways that are hard to predict. They can copy misleading patterns from their training data, produce text that is too complex for a reader's needs, and retain private, outdated, or incorrect content. This project studies how…

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