scBench-Long is a benchmark with 21 evaluations where the strongest AI model-harness pair succeeds on 25.4% of long-horizon single-cell biology tasks.
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Introduces SpatialBench-Long benchmark with 24 evaluations on spatial biology datasets from PDAC, glioblastoma, lung adenocarcinoma and optic nerve systems, reporting top model performance at 8/72 runs (11.1%).
MEDAL distills manifold embeddings into autoencoders to enable out-of-sample extension and held-out validation of dimension reduction methods.
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scBench-Long: Verifiable Benchmarking of Long-Horizon Single-Cell Biology
scBench-Long is a benchmark with 21 evaluations where the strongest AI model-harness pair succeeds on 25.4% of long-horizon single-cell biology tasks.
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Verifiable Benchmarking of Long-Horizon Spatial Biology
Introduces SpatialBench-Long benchmark with 24 evaluations on spatial biology datasets from PDAC, glioblastoma, lung adenocarcinoma and optic nerve systems, reporting top model performance at 8/72 runs (11.1%).
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MEDAL: Manifold Embedding Distillation via Autoencoder Learning
MEDAL distills manifold embeddings into autoencoders to enable out-of-sample extension and held-out validation of dimension reduction methods.