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Schmidt Sciences 2026 Interpretability RFP funds technical research on detecting and mitigating deceptive behaviors in large language models.
The program targets three primary directions: (1) Detection — developing tools to identify deceptive behaviors where model outputs contradict internal representations of truth; (2) Steering — creating targeted interventions to improve model truthfulness using mechanistic insights, outperforming traditional finetuning baselines; and (3) Applications — translating detection and steering techniques into practical improvements for human-AI collaboration, multi-agent systems, and decision support.
Deceptive behaviors include factually incorrect outputs, misleading confidence claims, fabrications, selective omissions, and other knowingly misleading conduct. Awards range from $300K to $1M with projects lasting 1-3 years.
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Search similar grants →Based on current listing details, eligibility includes: Open globally to individual researchers, research teams, research institutions, and multi-institution collaborations across universities, national laboratories, institutes, and nonprofit research organizations. Cross-border partnerships encouraged. Indirect costs cannot exceed 10%. Funded projects must comply with applicable law without lobbying or political activity. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates $300,000 to $1,000,000 per award inclusive of overhead up to 10%. Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
The current target date is May 26, 2026. Build your timeline backwards from this date to cover registrations, approvals, attachments, and final submission checks.
Federal grant success rates typically range from 10-30%, varying by agency and program. Build a strong proposal with clear objectives, measurable outcomes, and a well-justified budget to improve your chances.
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