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Find similar grantsOpenTrustLLM: An Open-Source Ecosystem for Trustworthiness in Large Language Models is sponsored by National Science Foundation (NSF). Establishes a community-driven framework to evaluate and enhance the trustworthiness of large language models.
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POSE: Phase I: OpenTrustLLM: An Open-Source Ecosystem for Trustworthiness in Large Language Models - National Science Foundation POSE: Phase I: OpenTrustLLM: An Open-Source Ecosystem for Trustworthiness in Large Language Models This Pathways to Enable Open-Source Ecosystems (POSE) project involves the creation of an open, community-driven framework to evaluate and enhance the trustworthiness of large language models (LLMs).
Large language models are increasingly utilized in sectors such as healthcare, finance, education, and national security, yet concerns about their reliability, safety, and transparency remain significant. This project establishes a collaborative ecosystem that enables stakeholders to assess trustworthiness using open standards and transparent processes.
By promoting confidence in artificial intelligence technologies, this project advances national health, economic growth, and benefits all Americans. The effort contributes to scientific and technological understanding by promoting rigorous evaluation practices and facilitating education around trustworthy artificial intelligence development.
The project strengthens United States leadership in artificial intelligence safety and reliability, benefiting academic researchers, industry professionals, government agencies, and the broader public through more dependable artificial intelligence applications.
This Pathways to Enable Open-Source Ecosystems (POSE) project revises an existing trustworthiness evaluation platform into a sustainable open-source ecosystem named OpenTrustLLM. The project addresses the challenge of fragmented trustworthiness evaluation methods by constructing a unified infrastructure with distributed community governance.
Key objectives include refactoring the current framework for modular contributions, developing continuous integration workflows, establishing a long-term governing committee, and expanding an engaged user and developer community. The project integrates multiple evaluation tools to cover critical trustworthiness dimensions such as robustness, privacy, and safety.
Technical approaches include open-source software engineering best practices, black-box evaluation protocols applicable to both proprietary and open-source large language models, and proactive community education. The outcome is a scalable and sustainable ecosystem that enables systematic trustworthiness assessment for a wide range of large language models deployed in real-world applications.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Program Director: Florence Rabanal Status Active Effective start/end date 08/15/25 → 07/31/27 Lead and Sub-Awardee Organization(s) (POSE) NSF Pathways to Enable Open-Source Ecosystems: $300,000.
00 (POSE) NSF Pathways to Enable Open-Source Ecosystems Advanced Computing and Semiconductors Machine Learning Training Data Artificial Intelligence (excluding ML) Advanced Computing and Semiconductors (Broad) Congressional District at Award District n. 07 of Pennsylvania Current Congressional District District n. 07 of Pennsylvania Core Based Statistical Area (CBSA) Allentown-Bethlehem-Easton, PA-NJ https://www.
nsf. gov/awardsearch/showAward? AWD_ID=2449280 Explore the research topics touched on by this project.
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elsevier. com/products/elsevier-fingerprint-engine Trustworthiness Evaluation Artificial Intelligence Applications
According to the current listing, eligibility includes: Universities. Confirm the full requirements in the official notice before applying.
The current listing shows $300,000. Verify award ceilings, matching requirements, and allowable costs in the official notice.
OpenTrustLLM: An Open-Source Ecosystem for Trustworthiness in Large Language Models is funded by National Science Foundation (NSF). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
MGPV Travel Grant is sponsored by Geological Society of America (GSA), Mineralogy, Geochemistry, Petrology, Volcanology Division. MGPV Travel grants support student travel to the annual GSA meeting. Applications are restricted to active graduate or undergraduate students who are the presenting authors of an accepted abstract at the annual GSA meeting.
Research Opportunities in Space and Earth Science (ROSES) - 2025: A.4 Rapid Response and Novel Research in Earth Science is sponsored by National Aeronautics and Space Administration (NASA) Science Mission Directorate (SMD). This omnibus research funding opportunity includes various program elements, with rolling submissions for Earth Science research through August 2026. Proposers to Earth Science using the NASA Center for Climate Simulation high-end computing facility must include specific budget details.
TCUP lists eight funding tracks and roughly $10.3M a year, but the October 14, 2026 deadline applies to only three of them — CHAI, Pre-TI, and TCUP Partnerships — and each carries a restriction that disqualifies most applicants. Here is the track-by-track math.
Read articleNSF 26-513 makes roughly $100 million available for up to 10 State and Regional AI Infrastructure Hubs at $4M to $12M each over five years. One award per state or multi-state region. One proposal per organization. And NSF is not buying you GPUs — it funds the coordination, the workforce and the faculty training, while the compute has to come from partners you have to already have.
Read articleAs of September 12, NSF had obligated $6.3 billion across 6,200 grants versus $8.1 billion and 8,600 last year. AHRQ has made 61 awards. Judge Allison Burroughs ordered the government to report by September 28 on whether IES will obligate $180 million before it expires. Here is what actually happens to the money on October 1 — and what it means for your FY2027 application.
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