{"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/towards-deep-learning-models-resistant-to","title":"Towards Deep Learning Models Resistant to Adversarial Attacks","arxiv_id":"1706.06083","date":"2017-06-19","proceeding":"ICLR 2018 1","authors":["Aleksander Madry","Aleksandar Makelov","Ludwig Schmidt","Dimitris Tsipras","Adrian Vladu"],"abstract":"Recent work has demonstrated that deep neural networks are vulnerable to adversarial examples---inputs that are almost indistinguishable from natural data and yet classified incorrectly by the network. In fact, some of the latest findings suggest that the existence of adversarial attacks may be an inherent weakness of deep learning models. To address this problem, we study the adversarial robustness of neural networks through the lens of robust optimization. This approach provides us with a broad and unifying view on much of the prior work on this topic. Its principled nature also enables us to identify methods for both training and attacking neural networks that are reliable and, in a certain sense, universal. In particular, they specify a concrete security guarantee that would protect against any adversary. These methods let us train networks with significantly improved resistance to a wide range of adversarial attacks. They also suggest the notion of security against a first-order adversary as a natural and broad security guarantee. We believe that robustness against such well-defined classes of adversaries is an important stepping stone towards fully resistant deep learning models. Code and pre-trained models are available at https://github.com/MadryLab/mnist_challenge and https://github.com/MadryLab/cifar10_challenge.","url_abs":"https://arxiv.org/abs/1706.06083v4","url_pdf":"https://arxiv.org/pdf/1706.06083v4.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":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/MadryLab/cifar10_challenge","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/MadryLab/mnist_challenge","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/AI-secure/Transferability-Reduced-Smooth-Ensemble","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/EPFL-VILAB/XDEnsembles","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/Hadisalman/robust-verify-benchmark","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/Jeffkang-94/pytorch-adversarial-attack","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/KnowledgeDiscovery/FaceSec","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/P2333/Max-Mahalanobis-Training","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/SafiyaJan/Attacking-Neural-Networks","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/TonyYaoMSU/ProjectedGradientDescent","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/VishaalMK/VectorDefense","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/Zoky-2020/Set-level_Guidance_Attack","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/abahram77/mnistChallenge","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/abahram77/mnist_challenge","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/albertmillan/adversarial-training-pytorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/amerch/CIFAR100-Training","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/andrewilyas/ens-adv-train-attack","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/arobey1/advbench","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/arobey1/mbrdl","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/bethgelab/cifar10_challenge","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/bingcheng45/hnr-extension","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/boyellow/adaad","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/cdluminate/advrank","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/cdluminate/advrank-pub","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/cleverhans-lab/cleverhans","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/cs-giung/course-dl-TP","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/dacostaHugo/Adversarial_attacks","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/ee17b031-iittp/Projected-Gradient-Descent-with-CIFAR10","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/eldadp100/Towards-Deep-Learning-Models-Resistant-to-Adversarial-Attacks-Implementation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/eldadp100/cnn_course_final","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/henry8527/GCE","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/hope-yao/robust_attention_cifar","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/hrdwsong/TDLMR2AA-Paddle","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"paddle","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/jokeryan/post_training","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/khieu/cifar10_challenge","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/lemonadec/Relevance-between-Accuracy-under-Black-box-Attack-and-the-Similarity-between-Networks","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/locuslab/convex_adversarial","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/locuslab/robust_overfitting","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/loes5307/vocaladversary2022","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/luizgh/adversarial_signatures","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/matanbt/attack-tabular","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/microsoft/distance-learner","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/ndb796/pytorch-adversarial-training-cifar","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/openai/cleverhans","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/peck94/cann-detector","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/revbucket/mister_ed","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/scenarri/s2m-tea","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/shashankskagnihotri/adv-corrected-ddcat-cospgd","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/tensorflow/cleverhans","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/thomashopkins32/PGDAdversarialLearning","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/tianzheng4/Distributionally-Adversarial-Attack","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/ucsb-nlp-chang/textgrad","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/val-iisc/flss","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/zibojia/rslad","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/zjfheart/Friendly-Adversarial-Training","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/Cadden/paddle-adver","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"paddle","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/YinDFY/PGD_for_targeted_attack","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/imrahulr/adversarial_robustness_pytorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"towards-deep-learning-models-resistant-to","repo_url":"https://github.com/salomonhotegni/MOREL","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"adversarial-attack","task_name":"Adversarial Attack"},{"task_slug":"adversarial-defense","task_name":"Adversarial Defense"},{"task_slug":"adversarial-robustness","task_name":"Adversarial Robustness"},{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"part-of-speech-tagging","task_name":"Part-Of-Speech Tagging"},{"task_slug":"robust-classification","task_name":"Robust classification"},{"task_slug":"sound-event-detection","task_name":"Sound Event Detection"},{"task_slug":"video-quality-assessment","task_name":"Video Quality Assessment"}],"methods":[{"method_slug":null,"method_name":null}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/adversarial-attack-on-cifar-10","task":"Adversarial Attack","dataset":"CIFAR-10","model":"AdvTraining [madry2018]","rank_in_archive_order":2,"of":6,"metrics":{"Attack: PGD20":"48.440"},"uses_additional_data":false},{"leaderboard":"/sota/part-of-speech-tagging-on-morphosyntactic","task":"Part-Of-Speech Tagging","dataset":"Morphosyntactic-analysis-dataset","model":"MyBert","rank_in_archive_order":1,"of":1,"metrics":{"BLEX":"77.21"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1706.06083","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1706.06083"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+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/tensorflow/cleverhans","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/Hadisalman/robust-verify-benchmark","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/shashankskagnihotri/adv-corrected-ddcat-cospgd","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/zjfheart/Friendly-Adversarial-Training","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/andrewilyas/ens-adv-train-attack","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/KnowledgeDiscovery/FaceSec","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/ucsb-nlp-chang/textgrad","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/cdluminate/advrank-pub","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/amerch/CIFAR100-Training","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/eldadp100/Towards-Deep-Learning-Models-Resistant-to-Adversarial-Attacks-Implementation","reach":{"status":"unanswered"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/dacostaHugo/Adversarial_attacks","reach":{"status":"unanswered"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/cdluminate/advrank","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/Cadden/paddle-adver","reach":{"status":"unanswered"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/TonyYaoMSU/ProjectedGradientDescent","reach":{"status":"unanswered"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/jokeryan/post_training","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/YinDFY/PGD_for_targeted_attack","reach":{"status":"unanswered"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/locuslab/convex_adversarial","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/scenarri/s2m-tea","reach":{"status":"ok","spdx":"Apache-2.0"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/arobey1/mbrdl","reach":{"status":"ok","spdx":"NOASSERTION"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/ndb796/pytorch-adversarial-training-cifar","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/loes5307/vocaladversary2022","reach":{"status":"unanswered"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/AI-secure/Transferability-Reduced-Smooth-Ensemble","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/EPFL-VILAB/XDEnsembles","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/locuslab/robust_overfitting","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/peck94/cann-detector","reach":{"status":"ok"}}],"summary":{"ran_draft_wrong":6,"ran_fixture":1,"ran_honours":2,"unverified":8},"by_repo_kind":{"listed":{"samples":9,"ran":3,"repositories":3}},"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":13,"samples":[{"code_sha256_prefix":"57555b28180e36f9","entry":"attack_pgd","repo":"zibojia/rslad","repo_kind":"listed","path":"rslad_loss.py","file_url":"https://github.com/zibojia/rslad/blob/HEAD/rslad_loss.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"57555b28180e36f9"}},{"code_sha256_prefix":"583f9780bdd00a45","entry":"conv3x3","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"583f9780bdd00a45"}},{"code_sha256_prefix":"9960f247d801fa2a","entry":"kl_loss","repo":"zibojia/rslad","repo_kind":"listed","path":"mobilenet_v2_rslad_cifar10.py","file_url":"https://github.com/zibojia/rslad/blob/HEAD/mobilenet_v2_rslad_cifar10.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"9960f247d801fa2a"}},{"code_sha256_prefix":"33ba52fc17e89516","entry":"mixup_criterion","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"33ba52fc17e89516"}},{"code_sha256_prefix":"b20f1357b1d8dbf8","entry":"mixup_data","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"b20f1357b1d8dbf8"}},{"code_sha256_prefix":"11b0ec76b88d8553","entry":"mixup_data","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"11b0ec76b88d8553"}},{"code_sha256_prefix":"dc3545f86c25dbe2","entry":"pseudorandom_target","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"dc3545f86c25dbe2"}},{"code_sha256_prefix":"108e0e470de94dfe","entry":"pseudorandom_target_image","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"108e0e470de94dfe"}},{"code_sha256_prefix":"d4a9a69d1dba912f","entry":"rslad_inner_loss","repo":"zibojia/rslad","repo_kind":"listed","path":"rslad_loss.py","file_url":"https://github.com/zibojia/rslad/blob/HEAD/rslad_loss.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"d4a9a69d1dba912f"}},{"code_sha256_prefix":"f0d4b8c8f55455d1","entry":"MART_loss","repo":"zjfheart/Friendly-Adversarial-Training","repo_kind":"listed","path":"FAT_for_MART.py","file_url":"https://github.com/zjfheart/Friendly-Adversarial-Training/blob/HEAD/FAT_for_MART.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"f0d4b8c8f55455d1"}},{"code_sha256_prefix":"310d3d6ec0329c05","entry":"TRADES_loss","repo":"zjfheart/Friendly-Adversarial-Training","repo_kind":"listed","path":"FAT_for_TRADES.py","file_url":"https://github.com/zjfheart/Friendly-Adversarial-Training/blob/HEAD/FAT_for_TRADES.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"310d3d6ec0329c05"}},{"code_sha256_prefix":"ed8707d32cea6f61","entry":"adjust_tau","repo":"zjfheart/Friendly-Adversarial-Training","repo_kind":"listed","path":"FAT.py","file_url":"https://github.com/zjfheart/Friendly-Adversarial-Training/blob/HEAD/FAT.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"ed8707d32cea6f61"}},{"code_sha256_prefix":"9257b5b1f6195ecf","entry":"adjust_tau","repo":"zjfheart/Friendly-Adversarial-Training","repo_kind":"listed","path":"FAT_for_TRADES.py","file_url":"https://github.com/zjfheart/Friendly-Adversarial-Training/blob/HEAD/FAT_for_TRADES.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"9257b5b1f6195ecf"}},{"code_sha256_prefix":"102fe6c0dc1d18bc","entry":"adjust_tau","repo":"zjfheart/Friendly-Adversarial-Training","repo_kind":"listed","path":"FAT_for_MART.py","file_url":"https://github.com/zjfheart/Friendly-Adversarial-Training/blob/HEAD/FAT_for_MART.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"102fe6c0dc1d18bc"}},{"code_sha256_prefix":"8a93e041134b597a","entry":"clamp","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"8a93e041134b597a"}},{"code_sha256_prefix":"3918fb83399cf118","entry":"evaluate_baseline","repo":"locuslab/convex_adversarial","repo_kind":"listed","path":"examples/trainer.py","file_url":"https://github.com/locuslab/convex_adversarial/blob/HEAD/examples/trainer.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"3918fb83399cf118"}},{"code_sha256_prefix":"197a1c1869bf9116","entry":"get_image","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"197a1c1869bf9116"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}