Datasets › Wild-Time
Wild-Time
Wild-Time is a benchmark of 5 datasets that reflect temporal distribution shifts arising in a variety of real-world applications, including patient prognosis and news classification. On these datasets, we systematically benchmark 13 prior approaches, including methods in domain generalization, continual learning, self-supervised learning, and ensemble learning.
Source: Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time
Image Source: https://arxiv.org/pdf/2211.14238v1.pdf
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 6 papers for it but never published that list.
Dataset loaders archive 2025-07-28
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Tasks archive 2025-07-28
License archive 2025-07-28
Modalities archive 2025-07-28
Languages archive 2025-07-28
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Variants archive 2025-07-28
- Wild-Time
1 variant name, as the archive lists them.
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