{"url":"/dataset/xai-bench","name":"XAI-Bench","full_name":null,"description_markdown":"**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.","description_withheld":null,"homepage":"","introduced_date":"2021-06-23","introduced_date_note":null,"introduced_by":{"paper":"/paper/synthetic-benchmarks-for-scientific-research","title":"Synthetic Benchmarks for Scientific Research in Explainable Machine Learning","first_author":"Yang Liu","url":null},"license":{"name":"Unknown","url":null},"modalities":[],"tasks":[{"name":"Explainable artificial intelligence","url":"/task/explainable-artificial-intelligence","datasets_with_task":"/datasets/task/explainable-artificial-intelligence"}],"languages":[],"variants":["XAI-Bench"],"data_loaders":[],"num_papers_in_archive":8,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}