| cff-version: 1.2.0 | |
| message: "If you cite DotCheck engines or measured holdout gates, use the citation below." | |
| title: "DotCheck AI-likeness engines (inhouse@5, inhouse-text@9, inhouse-video@2)" | |
| authors: | |
| - name: "DotCheck" | |
| url: "https://dotcheck.ai" | |
| repository-code: "https://huggingface.co/DotCheck" | |
| license: "Apache-2.0" | |
| date-released: "2026-07-26" | |
| abstract: >- | |
| DotCheck serves binary AI-likeness scores for images (wire inhouse@5 / | |
| Vermeer), text (inhouse-text@9 / Valla, seven languages), and video frame | |
| bags (inhouse-video@2 / Muybridge) using linear/logistic heads on frozen | |
| commercial-clean backbones. Live heads are published under Apache-2.0 on | |
| Hugging Face; everyday product scoring runs through DotCheck. | |
| keywords: | |
| - ai-detection | |
| - image-classification | |
| - text-classification | |
| - video | |
| - siglip2 | |
| preferred-citation: | |
| type: soft | |
| authors: | |
| - name: "DotCheck" | |
| title: "DotCheck engines (inhouse@5, inhouse-text@9, inhouse-video@2)" | |
| url: "https://dotcheck.ai/docs" | |
| year: 2026 | |