{"url":"/dataset/nats-bench","name":"NATS-Bench","full_name":null,"description_markdown":"A unified benchmark on searching for both topology and size, for (almost) any up-to-date NAS algorithm. NATS-Bench includes the search space of 15,625 neural cell candidates for architecture topology and 32,768 for architecture size on three datasets. \r\n\r\nSource: [NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size](/paper/nats-bench-benchmarking-nas-algorithms-for)","description_withheld":null,"homepage":"https://xuanyidong.com/assets/projects/NATS-Bench","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/nats-bench-benchmarking-nas-algorithms-for","title":"NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size","first_author":"Xuanyi Dong","url":null},"license":null,"modalities":[],"tasks":[{"name":"Neural Architecture Search","url":"/task/architecture-search","datasets_with_task":"/datasets/task/architecture-search"}],"languages":[],"variants":["NATS-Bench Topology, ImageNet16-120","NATS-Bench Topology, CIFAR-100","NATS-Bench Topology, CIFAR-10","NATS-Bench Size, ImageNet16-120","NATS-Bench Size","NATS-Bench Size, CIFAR-100","NATS-Bench Size, CIFAR-10","NATS-Bench"],"data_loaders":[],"num_papers_in_archive":43,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/neural-architecture-search-on-nats-bench","task":"Neural Architecture Search","dataset_variant":"NATS-Bench Topology, ImageNet16-120","rows":11,"metrics":["Test Accuracy","Kendall's Tau","Spearman's Rho"],"first_row_in_archive_order":{"model":"LayerNAS","paper":"/paper/layernas-neural-architecture-search-in","metrics":{"Test Accuracy":"46.58±0.59"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/neural-architecture-search-on-nats-bench-1","task":"Neural Architecture Search","dataset_variant":"NATS-Bench Topology, CIFAR-10","rows":11,"metrics":["Test Accuracy","Kendall's Tau","Spearman's Rho"],"first_row_in_archive_order":{"model":"LayerNAS","paper":"/paper/layernas-neural-architecture-search-in","metrics":{"Test Accuracy":"94.34±0.12"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/neural-architecture-search-on-nats-bench-2","task":"Neural Architecture Search","dataset_variant":"NATS-Bench Topology, CIFAR-100","rows":11,"metrics":["Test Accuracy","Kendall's Tau","Spearman's Rho"],"first_row_in_archive_order":{"model":"LayerNAS","paper":"/paper/layernas-neural-architecture-search-in","metrics":{"Test Accuracy":"73.01±0.63"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/neural-architecture-search-on-nats-bench-size-2","task":"Neural Architecture Search","dataset_variant":"NATS-Bench Size, CIFAR-100","rows":5,"metrics":["Kendall's Tau","Spearman's Rho","Pearson R","Acc. (test)","Test Accuracy","Validation Accuracy"],"first_row_in_archive_order":{"model":"GreenMachine-2","paper":"/paper/greenmachine-automatic-design-of-zero-cost","metrics":{"Kendall's Tau":"0.769","Spearman's Rho":"0.924"},"code_links":[{"title":"RodriguesGabriel/greenmachine","url":"https://github.com/RodriguesGabriel/greenmachine"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/neural-architecture-search-on-nats-bench-size-3","task":"Neural Architecture Search","dataset_variant":"NATS-Bench Size, ImageNet16-120","rows":4,"metrics":["Kendall's Tau","Spearman's Rho","Test Accuracy","Validation Accuracy"],"first_row_in_archive_order":{"model":"GreenMachine-2","paper":"/paper/greenmachine-automatic-design-of-zero-cost","metrics":{"Kendall's Tau":"0.856","Spearman's Rho":"0.971"},"code_links":[{"title":"RodriguesGabriel/greenmachine","url":"https://github.com/RodriguesGabriel/greenmachine"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/greenmachine-automatic-design-of-zero-cost","title":"GreenMachine: Automatic Design of Zero-Cost Proxies for Energy-Efficient NAS","date":"2024-11-22","rows_on_this_dataset":15,"code_links":1,"syntology":null},{"paper":"/paper/layernas-neural-architecture-search-in","title":"LayerNAS: Neural Architecture Search in Polynomial Complexity","date":"2023-04-23","rows_on_this_dataset":5,"code_links":0,"syntology":null},{"paper":"/paper/generalization-properties-of-nas-under","title":"Generalization Properties of NAS under Activation and Skip Connection Search","date":"2022-09-15","rows_on_this_dataset":3,"code_links":0,"syntology":null},{"paper":"/paper/knas-green-neural-architecture-search","title":"KNAS: Green Neural Architecture Search","date":"2021-11-26","rows_on_this_dataset":3,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":6,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/nasi-label-and-data-agnostic-neural","title":"NASI: Label- and Data-agnostic Neural Architecture Search at Initialization","date":"2021-09-02","rows_on_this_dataset":3,"code_links":0,"syntology":null},{"paper":"/paper/bossnas-exploring-hybrid-cnn-transformers","title":"BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search","date":"2021-03-23","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/neural-architecture-search-on-imagenet-in-1","title":"Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective","date":"2021-02-23","rows_on_this_dataset":3,"code_links":4,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":2,"samples_unverified":2,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/fairnas-rethinking-evaluation-fairness-of","title":"FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture Search","date":"2019-07-03","rows_on_this_dataset":3,"code_links":2,"syntology":null},{"paper":"/paper/regularized-evolution-for-image-classifier","title":"Regularized Evolution for Image Classifier Architecture Search","date":"2018-02-05","rows_on_this_dataset":3,"code_links":5,"syntology":null},{"paper":"/paper/proximal-policy-optimization-algorithms","title":"Proximal Policy Optimization Algorithms","date":"2017-07-20","rows_on_this_dataset":3,"code_links":188,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":176,"samples_ran":99,"samples_unverified":77,"pointer_only_for_licence":94,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":3,"samples_harvested":187,"samples_ran":107,"samples_unverified":80,"pointer_only_for_licence":96,"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."}