Datasets › Wild-Time

Wild-Time

Introduced by Huaxiu Yao et al. in Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time25 Nov 2022 archive 2025-07-28

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

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

MIT License

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • Wild-Time

1 variant name, as the archive lists them.

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