{"about":{"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.","site":"https://codewithpapers.app","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","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/method/fixmatch/papers/ran/1","list_of":"/method/fixmatch","method":"FixMatch","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"ran","order_definition":"only papers where Syntology ran at least one harvested sample; date (newest first), ties by arXiv id","caption":"We ran code from the paper's repository; we did not isolate this method inside it.","absence":"A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.","page":1,"pages_in_order":1,"rows_per_page":100,"rows":[1,19],"of":19,"counts":{"archive_papers_tagged":85,"with_a_code_link":44,"where_syntology_ran_a_sample":19,"not_listed_spam_title":0,"listed":85,"listed_where_code_ran":19,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":15,"every_run_a_failure_of_syntologys_instrument":4,"listed_with_a_run_with_no_instrument_failure":15,"listed_every_run_a_failure_of_syntologys_instrument":4,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/method/fixmatch/papers/ran/1","prev":null,"next":null,"papers":[{"paper":"/paper/rankup-boosting-semi-supervised-regression","slug":"rankup-boosting-semi-supervised-regression","title":"RankUp: Boosting Semi-Supervised Regression with an Auxiliary Ranking Classifier","date":"2024-10-29","arxiv_id":"2410.22124","n_code_links":1,"syntology":{"ran":9,"of":9,"n_ran_checked":6,"n_instrument":3,"unverified":0,"pointer_only":4,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["pm25/semi-supervised-regression"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/2408-02192","slug":"2408-02192","title":"Unsupervised Domain Adaption Harnessing Vision-Language Pre-training","date":"2024-08-05","arxiv_id":"2408.02192","n_code_links":1,"syntology":{"ran":6,"of":13,"n_ran_checked":3,"n_instrument":3,"unverified":7,"pointer_only":5,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 3 where Syntology's instrument failed) · 7 unverified","official":{"repos":["Wenlve-Zhou/VLP-UDA"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":7,"ran_from_kinds":["official"]}}},{"paper":"/paper/enhancing-sample-utilization-through-sample","slug":"enhancing-sample-utilization-through-sample","title":"Enhancing Sample Utilization through Sample Adaptive Augmentation in Semi-Supervised Learning","date":"2023-09-07","arxiv_id":"2309.03598","n_code_links":1,"syntology":{"ran":4,"of":5,"n_ran_checked":1,"n_instrument":3,"unverified":1,"pointer_only":5,"phrase":"4 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","official":{"repos":["guangui-nju/saa"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/relationmatch-matching-in-batch-relationships","slug":"relationmatch-matching-in-batch-relationships","title":"RelationMatch: Matching In-batch Relationships for Semi-supervised Learning","date":"2023-05-17","arxiv_id":"2305.10397","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["yifanzhang-pro/relationmatch"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/boosting-semi-supervised-learning-by","slug":"boosting-semi-supervised-learning-by","title":"Boosting Semi-Supervised Learning by Exploiting All Unlabeled Data","date":"2023-03-20","arxiv_id":"2303.11066","n_code_links":1,"syntology":{"ran":6,"of":6,"n_ran_checked":6,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 1 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["megvii-research/fullmatch"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/revisiting-weak-to-strong-consistency-in-semi","slug":"revisiting-weak-to-strong-consistency-in-semi","title":"Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation","date":"2022-08-21","arxiv_id":"2208.09910","n_code_links":1,"syntology":{"ran":7,"of":9,"n_ran_checked":4,"n_instrument":3,"unverified":2,"pointer_only":6,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified","official":{"repos":["LiheYoung/UniMatch"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/usb-a-unified-semi-supervised-learning","slug":"usb-a-unified-semi-supervised-learning","title":"USB: A Unified Semi-supervised Learning Benchmark for Classification","date":"2022-08-12","arxiv_id":"2208.07204","n_code_links":5,"syntology":{"ran":9,"of":9,"n_ran_checked":4,"n_instrument":5,"unverified":0,"pointer_only":0,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 4 honoured, 0 violated, 0 with no contract checked; 5 where Syntology's instrument failed) · 0 unverified","official":{"repos":["microsoft/semi-supervised-learning"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/class-aware-contrastive-semi-supervised","slug":"class-aware-contrastive-semi-supervised","title":"Class-Aware Contrastive Semi-Supervised Learning","date":"2022-03-04","arxiv_id":"2203.02261","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":2,"n_instrument":0,"unverified":1,"pointer_only":3,"phrase":"2 ran (of which 1 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["tencentyouturesearch/classification-semicls"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/debiased-learning-from-naturally-imbalanced","slug":"debiased-learning-from-naturally-imbalanced","title":"Debiased Learning from Naturally Imbalanced Pseudo-Labels","date":"2022-01-05","arxiv_id":"2201.01490","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["frank-xwang/debiased-pseudo-labeling"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/semi-supervised-learning-with-taxonomic","slug":"semi-supervised-learning-with-taxonomic","title":"Semi-Supervised Learning with Taxonomic Labels","date":"2021-11-23","arxiv_id":"2111.11595","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["cvl-umass/ssl-evaluation"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/flexmatch-boosting-semi-supervised-learning","slug":"flexmatch-boosting-semi-supervised-learning","title":"FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling","date":"2021-10-15","arxiv_id":"2110.08263","n_code_links":2,"syntology":{"ran":4,"of":6,"n_ran_checked":1,"n_instrument":3,"unverified":2,"pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified","official":{"repos":["torchssl/torchssl"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/data-centric-semi-supervised-learning","slug":"data-centric-semi-supervised-learning","title":"Unsupervised Selective Labeling for More Effective Semi-Supervised Learning","date":"2021-10-06","arxiv_id":"2110.03006","n_code_links":1,"syntology":{"ran":7,"of":8,"n_ran_checked":6,"n_instrument":1,"unverified":1,"pointer_only":2,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["TonyLianLong/UnsupervisedSelectiveLabeling"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/opencos-contrastive-semi-supervised-learning-1","slug":"opencos-contrastive-semi-supervised-learning-1","title":"OpenCoS: Contrastive Semi-supervised Learning for Handling Open-set Unlabeled Data","date":"2021-06-29","arxiv_id":"2107.08943","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["alinlab/opencos"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/semi-supervised-domain-generalization-with","slug":"semi-supervised-domain-generalization-with","title":"Semi-Supervised Domain Generalization with Stochastic StyleMatch","date":"2021-06-01","arxiv_id":"2106.00592","n_code_links":2,"syntology":{"ran":4,"of":4,"n_ran_checked":2,"n_instrument":2,"unverified":0,"pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["KaiyangZhou/Dassl.pytorch","KaiyangZhou/ssdg-benchmark"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/openmatch-open-set-consistency-regularization","slug":"openmatch-open-set-consistency-regularization","title":"OpenMatch: Open-set Consistency Regularization for Semi-supervised Learning with Outliers","date":"2021-05-28","arxiv_id":"2105.14148","n_code_links":1,"syntology":{"ran":15,"of":19,"n_ran_checked":11,"n_instrument":4,"unverified":4,"pointer_only":7,"phrase":"15 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 1 violated, 10 with no contract checked; 4 where Syntology's instrument failed) · 4 unverified","official":{"repos":["VisionLearningGroup/OP_Match"],"state":"official (archive's flag): 15 ran","n_ran":15,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":"/paper/adaptive-consistency-regularization-for-semi","slug":"adaptive-consistency-regularization-for-semi","title":"Adaptive Consistency Regularization for Semi-Supervised Transfer Learning","date":"2021-03-03","arxiv_id":"2103.02193","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":1,"n_instrument":2,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["SHI-Labs/Semi-Supervised-Transfer-Learning"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/sinkhorn-label-allocation-semi-supervised","slug":"sinkhorn-label-allocation-semi-supervised","title":"Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training","date":"2021-02-17","arxiv_id":"2102.08622","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["stanford-futuredata/sinkhorn-label-allocation"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/comatch-semi-supervised-learning-with","slug":"comatch-semi-supervised-learning-with","title":"CoMatch: Semi-supervised Learning with Contrastive Graph Regularization","date":"2020-11-23","arxiv_id":"2011.11183","n_code_links":3,"syntology":{"ran":2,"of":3,"n_ran_checked":0,"n_instrument":2,"unverified":1,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["salesforce/CoMatch"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/fixmatch-simplifying-semi-supervised-learning","slug":"fixmatch-simplifying-semi-supervised-learning","title":"FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence","date":"2020-01-21","arxiv_id":"2001.07685","n_code_links":26,"syntology":{"ran":53,"of":74,"n_ran_checked":35,"n_instrument":18,"unverified":21,"pointer_only":17,"phrase":"53 ran (of which 13 constructed an object rather than computing a result; 35 with no instrument failure: 3 honoured, 2 violated, 30 with no contract checked; 18 where Syntology's instrument failed) · 21 unverified","official":{"repos":["google-research/fixmatch"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}}],"record_sha256":"939a89ca5c07b07b59ed5f0ba272188adbddbdcb26cb3e8215111ed965cd26f0","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}