Index
Grant: ARIA TA1.1: Employing Categorical Probability Towards Safe AI (Advanced Research and Invention Agency (ARIA) → University of Oxford)
Verdictconfirmed95%
2 checks · 1 src · 4/13/2026⚠ Checks disagree: 1 confirmed, 1 unverifiable
Deterministic match: grantee, name matched in source snapshot (48 rows)
Our claim
entire record- Grantee
- University of Oxford
- Name
- ARIA TA1.1: Employing Categorical Probability Towards Safe AI
- Currency
- GBP
- Date
- January 2024
- Notes
- [Safeguarded AI TA1.1] Employing Categorical Probability Towards Safe AI. Lead(s): Sam Staton, Pedro Amorim, Elena Di Lavore, Paolo Perrone, Mario Roman, Ruben Van Belle, Younesse Kaddar, Jack Liell-Cock, Owen Lynch. Institutions: University of Oxford. Status: active.
Source evidence
1 src · 2 checksconfirmed95%deterministic-row-match · 4/13/2026
- Grantee
- University of Oxford
- Focus Area
- TA1.1
- Name
- Employing Categorical Probability Towards Safe AI
- Description
- University of Oxford
- Status
- active
NoteDeterministic match: grantee, name matched in source snapshot (48 rows)
unverifiable85%Haiku 4.5 · 3/25/2026
NoteWhile the source confirms the existence of TA1 within the Safeguarded AI programme and discusses TA1 objectives, it does not provide information about the specific grant record being verified. The source does not mention the grant name, the date (2024-01), the grantee identifier (18K3KG3bpg), or the funder identifier (XqjV4mbMXQ). Without explicit confirmation of these specific details in the source text, the record cannot be verified.
Case № 26Ku1c2aAIFiled 4/13/2026Confidence 95%