TabPFN-MT: A Natively Multitask In-Context Learner for Tabular Data

In three linesTabPFN-MT extends Prior-Data Fitted Networks to multitask in-context learning for tabular data. Trained on multi-target synthetics, the model captures inter-task dependencies and reduces inference from O(T) to O(1) forward passes. On 344 datasets (<1000 samples), it achieves rank 4.89 in multitask accuracy, competitive with single-task ensembles.

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