{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/darts-robustly-stepping-out-of-performance","title":"DARTS-: Robustly Stepping out of Performance Collapse Without Indicators","arxiv_id":"2009.01027","date":"2020-09-02","proceeding":"ICLR 2021 1","authors":["Xiangxiang Chu","Xiaoxing Wang","Bo Zhang","Shun Lu","Xiaolin Wei","Junchi Yan"],"abstract":"Despite the fast development of differentiable architecture search (DARTS), it suffers from long-standing performance instability, which extremely limits its application. Existing robustifying methods draw clues from the resulting deteriorated behavior instead of finding out its causing factor. Various indicators such as Hessian eigenvalues are proposed as a signal to stop searching before the performance collapses. However, these indicator-based methods tend to easily reject good architectures if the thresholds are inappropriately set, let alone the searching is intrinsically noisy. In this paper, we undertake a more subtle and direct approach to resolve the collapse. We first demonstrate that skip connections have a clear advantage over other candidate operations, where it can easily recover from a disadvantageous state and become dominant. We conjecture that this privilege is causing degenerated performance. Therefore, we propose to factor out this benefit with an auxiliary skip connection, ensuring a fairer competition for all operations. We call this approach DARTS-. Extensive experiments on various datasets verify that it can substantially improve robustness. Our code is available at https://github.com/Meituan-AutoML/DARTS- .","url_abs":"https://arxiv.org/abs/2009.01027v2","url_pdf":"https://arxiv.org/pdf/2009.01027v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"darts-robustly-stepping-out-of-performance","repo_url":"https://github.com/Meituan-AutoML/DARTS-","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"automl","task_name":"AutoML"},{"task_slug":"architecture-search","task_name":"Neural Architecture Search"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/neural-architecture-search-on-nas-bench-201-1","task":"Neural Architecture Search","dataset":"NAS-Bench-201, CIFAR-10","model":"DARTS-","rank_in_archive_order":21,"of":37,"metrics":{"Accuracy (Test)":"93.80","Accuracy (Val)":"91.03","Search time (s)":"11520"},"uses_additional_data":false},{"leaderboard":"/sota/neural-architecture-search-on-nas-bench-201-2","task":"Neural Architecture Search","dataset":"NAS-Bench-201, CIFAR-100","model":"DARTS-","rank_in_archive_order":22,"of":40,"metrics":{"Accuracy (Test)":"71.53","Accuracy (Val)":"71.36"},"uses_additional_data":false},{"leaderboard":"/sota/neural-architecture-search-on-nas-bench-201","task":"Neural Architecture Search","dataset":"NAS-Bench-201, ImageNet-16-120","model":"DARTS-","rank_in_archive_order":29,"of":49,"metrics":{"Accuracy (Test)":"45.12","Accuracy (Val)":"44.87"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/2009.01027","atlas_url":"https://app.syntology.ai/?focus=2009.01027","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2009.01027"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/Meituan-AutoML/DARTS-","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"unverified":8},"by_repo_kind":{"official":{"samples":8,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"469bf48752905889","entry":"accuracy","repo":"Meituan-AutoML/DARTS-","repo_kind":"official","path":"src/utils.py","file_url":"https://github.com/Meituan-AutoML/DARTS-/blob/HEAD/src/utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"469bf48752905889"}},{"code_sha256_prefix":"3e816289579cc9e9","entry":"count_parameters_in_MB","repo":"Meituan-AutoML/DARTS-","repo_kind":"official","path":"src/utils.py","file_url":"https://github.com/Meituan-AutoML/DARTS-/blob/HEAD/src/utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"3e816289579cc9e9"}},{"code_sha256_prefix":"a48bdfe2a6bf0357","entry":"gen_beta","repo":"Meituan-AutoML/DARTS-","repo_kind":"official","path":"plots/plot_beta_vs_valid_loss.py","file_url":"https://github.com/Meituan-AutoML/DARTS-/blob/HEAD/plots/plot_beta_vs_valid_loss.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"a48bdfe2a6bf0357"}},{"code_sha256_prefix":"30bb0400a2dd1188","entry":"get_moving_average_3","repo":"Meituan-AutoML/DARTS-","repo_kind":"official","path":"plots/eigen_dist.py","file_url":"https://github.com/Meituan-AutoML/DARTS-/blob/HEAD/plots/eigen_dist.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"30bb0400a2dd1188"}},{"code_sha256_prefix":"db90642e32525cb0","entry":"get_moving_average_5","repo":"Meituan-AutoML/DARTS-","repo_kind":"official","path":"plots/eigen_dist.py","file_url":"https://github.com/Meituan-AutoML/DARTS-/blob/HEAD/plots/eigen_dist.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"db90642e32525cb0"}},{"code_sha256_prefix":"35394520b14b68c3","entry":"read_json","repo":"Meituan-AutoML/DARTS-","repo_kind":"official","path":"plots/plot_beta_vs_valid_loss.py","file_url":"https://github.com/Meituan-AutoML/DARTS-/blob/HEAD/plots/plot_beta_vs_valid_loss.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"35394520b14b68c3"}},{"code_sha256_prefix":"de6f3cc2917b53d0","entry":"singleton","repo":"Meituan-AutoML/DARTS-","repo_kind":"official","path":"src/utils.py","file_url":"https://github.com/Meituan-AutoML/DARTS-/blob/HEAD/src/utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"de6f3cc2917b53d0"}},{"code_sha256_prefix":"101678ccfacaef06","entry":"stop_criteria","repo":"Meituan-AutoML/DARTS-","repo_kind":"official","path":"plots/eigen_dist.py","file_url":"https://github.com/Meituan-AutoML/DARTS-/blob/HEAD/plots/eigen_dist.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"101678ccfacaef06"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}