publication
Unsolved Problems in ML Safety
Metadata
| Source Table | publications |
| Source ID | LjYYgtFUTy |
| Description | Dan Hendrycks, Nicholas Carlini, John Schulman, Jacob Steinhardt, 2021-09 |
| Source URL | arxiv.org/abs/2109.13916 |
| Parent | Center for AI Safety (CAIS) |
| Children | — |
| Created | Mar 23, 2026, 2:46 PM |
| Updated | Mar 23, 2026, 2:46 PM |
| Synced | Mar 23, 2026, 2:46 PM |
Record Data
id | LjYYgtFUTy |
entityId | Center for AI Safety (CAIS)(organization) |
entityDisplayName | — |
resourceId | — |
title | Unsolved Problems in ML Safety |
authors | Dan Hendrycks, Nicholas Carlini, John Schulman, Jacob Steinhardt |
url | arxiv.org/abs/2109.13916 |
venue | — |
publishedDate | 2021-09 |
publicationType | paper |
citationCount | — |
isFlagship | Yes |
abstract | — |
source | arxiv.org/abs/2109.13916 |
notes | Defines 4 core challenges: robustness, monitoring, alignment, systemic safety |
Source Check Verdicts
confirmed99% confidence
Last checked: 4/3/2026
All key fields in the record are directly confirmed by the source text. The title, all four authors, their affiliations, the publication date (2021-09 matches the arXiv identifier 2109.13916), the URL, and the publication type (paper/preprint) are all accurate. The source is the actual paper itself, providing authoritative confirmation of all metadata.
Debug info
Thing ID: LjYYgtFUTy
Source Table: publications
Source ID: LjYYgtFUTy