Datasets › XAI-Bench

XAI-Bench

Introduced by Yang Liu et al. in Synthetic Benchmarks for Scientific Research in Explainable Machine Learning23 Jun 2021 archive 2025-07-28

XAI-Bench is a suite of synthetic datasets along with a library for benchmarking feature attribution algorithms. Unlike real-world datasets, synthetic datasets allow the efficient computation of conditional expected values that are needed to evaluate ground-truth Shapley values and other metrics. The synthetic datasets released offer a wide variety of parameters that can be configured to simulate real-world data.

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 8 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

Unknown

Modalities archive 2025-07-28

No modality tagged.

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • XAI-Bench

1 variant name, as the archive lists them.

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