SiatBioInf/SingleCell-Unseen-Benchmark
SingleCell-Unseen-Benchmark Overview SingleCell-Unseen-Benchmark is a large-scale unseen single-cell transcriptomic benchmark designed to systematically evaluate foundation models on cell identification and cell type tracing tasks.The benchmark covers tumor, stem, neural, and normal cell populations, with a particular emphasis on unseen data distributions, including rare cell types, cross-dataset generalization, and heterogeneous tumor states. In addition to… See the full description on the dataset page: https://huggingface.co/datasets/SiatBioInf/SingleCell-Unseen-Benchmark.
| Author / organization | SiatBioInf |
|---|---|
| License (as declared) | cc-by-4.0 |
| Downloads | 1.3K (as reported by Hugging Face) |
| Likes | 0 |
| Created | 9 January 2026 |
| Last updated at source | 13 January 2026 |
Recent changes
- 16 Oct 2026 Description: SingleCell-Unseen-Benchmark Overview SingleCell-Unseen-Benchmark is a large-scale unseen single-cell transcriptomic benchmark designed to systematically evaluate foundation models on cell identification and cell type tracing tasks.The bench → SingleCell-Unseen-Benchmark Overview SingleCell-Unseen-Benchmark is a large-scale unseen single-cell transcriptomic benchmark designed to systematically evaluate foundation models on cell identification and cell type tracing tasks.The bench
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