{"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":"/task/domain-adaptation/papers/ran/4","list_of":"/task/domain-adaptation","task":"Domain Adaptation","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"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 run it on this task or check it against the task's benchmarks.","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":4,"pages_in_order":6,"rows_per_page":100,"rows":[301,400],"of":517,"counts":{"archive_papers_tagged":6439,"with_a_code_link":2400,"where_syntology_ran_a_sample":517,"not_listed_spam_title":0,"listed":6439,"listed_where_code_ran":517,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":442,"every_run_a_failure_of_syntologys_instrument":75,"listed_with_a_run_with_no_instrument_failure":442,"listed_every_run_a_failure_of_syntologys_instrument":75,"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":"/task/domain-adaptation/papers/ran/1","prev":"/task/domain-adaptation/papers/ran/3","next":"/task/domain-adaptation/papers/ran/5","papers":[{"url":"/paper/accuracy-on-the-line-on-the-strong","slug":"accuracy-on-the-line-on-the-strong","title":"Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization","date":"2021-07-09","arxiv_id":"2107.04649","repositories_listed":1,"syntology":{"n":4,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/accuracy-on-the-line-on-the-strong#ran","syntology_url":"https://syntology.ai/paper/2107.04649","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.04649"}},"official":null}},{"url":"/paper/cored-generalizing-fake-media-detection-with","slug":"cored-generalizing-fake-media-detection-with","title":"CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation","date":"2021-07-06","arxiv_id":"2107.02408","repositories_listed":2,"syntology":{"n":15,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":7,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":5,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/cored-generalizing-fake-media-detection-with#ran","syntology_url":"https://syntology.ai/paper/2107.02408","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.02408"}},"official":null}},{"url":"/paper/give-me-your-trained-model-domain-adaptive","slug":"give-me-your-trained-model-domain-adaptive","title":"A Curriculum-style Self-training Approach for Source-Free Semantic Segmentation","date":"2021-06-22","arxiv_id":"2106.11653","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"2 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; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/give-me-your-trained-model-domain-adaptive#ran","syntology_url":"https://syntology.ai/paper/2106.11653","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.11653"}},"official":{"repos":["yxiwang/atp"],"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","unlocated"]}}},{"url":"/paper/cuda-gr-controllable-unsupervised-domain","slug":"cuda-gr-controllable-unsupervised-domain","title":"CUDA-GHR: Controllable Unsupervised Domain Adaptation for Gaze and Head Redirection","date":"2021-06-21","arxiv_id":"2106.10852","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_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","sample_list":"/paper/cuda-gr-controllable-unsupervised-domain#ran","syntology_url":"https://syntology.ai/paper/2106.10852","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.10852"}},"official":{"repos":["jswati31/cuda-ghr"],"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"]}}},{"url":"/paper/f-domain-adversarial-learning-theory-and-1","slug":"f-domain-adversarial-learning-theory-and-1","title":"f-Domain-Adversarial Learning: Theory and Algorithms","date":"2021-06-21","arxiv_id":"2106.11344","repositories_listed":1,"syntology":{"n":5,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":5,"phrase":"2 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; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/f-domain-adversarial-learning-theory-and-1#ran","syntology_url":"https://syntology.ai/paper/2106.11344","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.11344"}},"official":null}},{"url":"/paper/revisiting-the-weaknesses-of-reinforcement-1","slug":"revisiting-the-weaknesses-of-reinforcement-1","title":"Revisiting the Weaknesses of Reinforcement Learning for Neural Machine Translation","date":"2021-06-16","arxiv_id":"2106.08942","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 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; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/revisiting-the-weaknesses-of-reinforcement-1#ran","syntology_url":"https://syntology.ai/paper/2106.08942","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.08942"}},"official":{"repos":["samuki/reinforce-joey"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/break-it-fix-it-unsupervised-learning-for","slug":"break-it-fix-it-unsupervised-learning-for","title":"Break-It-Fix-It: Unsupervised Learning for Program Repair","date":"2021-06-11","arxiv_id":"2106.06600","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 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; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/break-it-fix-it-unsupervised-learning-for#ran","syntology_url":"https://syntology.ai/paper/2106.06600","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.06600"}},"official":{"repos":["michiyasunaga/bifi"],"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"]}}},{"url":"/paper/adamatch-a-unified-approach-to-semi","slug":"adamatch-a-unified-approach-to-semi","title":"AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation","date":"2021-06-08","arxiv_id":"2106.04732","repositories_listed":6,"syntology":{"n":20,"n_ran":15,"n_constructed":5,"n_ran_checked":13,"n_instrument":2,"n_unverified":5,"n_honours":1,"n_violates":0,"n_no_contract":12,"n_pointer_only":10,"phrase":"15 ran (of which 5 constructed an object rather than computing a result; 13 with no instrument failure: 1 honoured, 0 violated, 12 with no contract checked; 2 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/adamatch-a-unified-approach-to-semi#ran","syntology_url":"https://syntology.ai/paper/2106.04732","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.04732"}},"official":{"repos":["google-research/adamatch"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/rda-robust-domain-adaptation-via-fourier","slug":"rda-robust-domain-adaptation-via-fourier","title":"RDA: Robust Domain Adaptation via Fourier Adversarial Attacking","date":"2021-06-05","arxiv_id":"2106.02874","repositories_listed":1,"syntology":{"n":10,"n_ran":6,"n_constructed":0,"n_ran_checked":4,"n_instrument":2,"n_unverified":4,"n_honours":2,"n_violates":0,"n_no_contract":2,"n_pointer_only":4,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 2 honoured, 0 violated, 2 with no contract checked; 2 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/rda-robust-domain-adaptation-via-fourier#ran","syntology_url":"https://syntology.ai/paper/2106.02874","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.02874"}},"official":null}},{"url":"/paper/category-contrast-for-unsupervised-domain","slug":"category-contrast-for-unsupervised-domain","title":"Category Contrast for Unsupervised Domain Adaptation in Visual Tasks","date":"2021-06-05","arxiv_id":"2106.02885","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":6,"n_instrument":2,"n_unverified":1,"n_honours":1,"n_violates":1,"n_no_contract":4,"n_pointer_only":2,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 1 honoured, 1 violated, 4 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/category-contrast-for-unsupervised-domain#ran","syntology_url":"https://syntology.ai/paper/2106.02885","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.02885"}},"official":{"repos":["jxhuang0508/CaCo"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/crowdsourcing-learning-as-domain-adaptation-a","slug":"crowdsourcing-learning-as-domain-adaptation-a","title":"Crowdsourcing Learning as Domain Adaptation: A Case Study on Named Entity Recognition","date":"2021-05-31","arxiv_id":"2105.14980","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/crowdsourcing-learning-as-domain-adaptation-a#ran","syntology_url":"https://syntology.ai/paper/2105.14980","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.14980"}},"official":{"repos":["izhx/CLasDA"],"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"]}}},{"url":"/paper/neural-machine-translation-with-monolingual","slug":"neural-machine-translation-with-monolingual","title":"Neural Machine Translation with Monolingual Translation Memory","date":"2021-05-24","arxiv_id":"2105.11269","repositories_listed":1,"syntology":{"n":15,"n_ran":8,"n_constructed":6,"n_ran_checked":6,"n_instrument":2,"n_unverified":7,"n_honours":1,"n_violates":0,"n_no_contract":5,"n_pointer_only":15,"phrase":"8 ran (of which 6 constructed an object rather than computing a result; 6 with no instrument failure: 1 honoured, 0 violated, 5 with no contract checked; 2 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/neural-machine-translation-with-monolingual#ran","syntology_url":"https://syntology.ai/paper/2105.11269","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.11269"}},"official":{"repos":["jcyk/copyisallyouneed"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":6,"n_ran_no_instrument_failure":6,"n_unverified":7,"ran_from_kinds":["official"]}}},{"url":"/paper/exploring-robustness-of-unsupervised-domain","slug":"exploring-robustness-of-unsupervised-domain","title":"Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation","date":"2021-05-23","arxiv_id":"2105.10843","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 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; 0 where Syntology's instrument failed) · 0 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/exploring-robustness-of-unsupervised-domain#ran","syntology_url":"https://syntology.ai/paper/2105.10843","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.10843"}},"official":{"repos":["uta-smile/ASSUDA"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/goo-a-dataset-for-gaze-object-prediction-in","slug":"goo-a-dataset-for-gaze-object-prediction-in","title":"GOO: A Dataset for Gaze Object Prediction in Retail Environments","date":"2021-05-22","arxiv_id":"2105.10793","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":1,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/goo-a-dataset-for-gaze-object-prediction-in#ran","syntology_url":"https://syntology.ai/paper/2105.10793","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.10793"}},"official":{"repos":["upeee/GOO-GAZE2021"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/learning-to-relate-depth-and-semantics-for","slug":"learning-to-relate-depth-and-semantics-for","title":"Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation","date":"2021-05-17","arxiv_id":"2105.07830","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":1,"n_ran_checked":3,"n_instrument":0,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":2,"n_pointer_only":4,"phrase":"3 ran (of which 1 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/learning-to-relate-depth-and-semantics-for#ran","syntology_url":"https://syntology.ai/paper/2105.07830","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.07830"}},"official":{"repos":["susaha/ctrl-uda"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":1,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/pixmatch-unsupervised-domain-adaptation-via","slug":"pixmatch-unsupervised-domain-adaptation-via","title":"PixMatch: Unsupervised Domain Adaptation via Pixelwise Consistency Training","date":"2021-05-17","arxiv_id":"2105.08128","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"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","sample_list":"/paper/pixmatch-unsupervised-domain-adaptation-via#ran","syntology_url":"https://syntology.ai/paper/2105.08128","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.08128"}},"official":{"repos":["lukemelas/pixmatch"],"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"]}}},{"url":"/paper/aggregating-from-multiple-target-shifted","slug":"aggregating-from-multiple-target-shifted","title":"Aggregating From Multiple Target-Shifted Sources","date":"2021-05-09","arxiv_id":"2105.04051","repositories_listed":1,"syntology":{"n":9,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/aggregating-from-multiple-target-shifted#ran","syntology_url":"https://syntology.ai/paper/2105.04051","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.04051"}},"official":null}},{"url":"/paper/self-supervised-augmentation-consistency-for","slug":"self-supervised-augmentation-consistency-for","title":"Self-supervised Augmentation Consistency for Adapting Semantic Segmentation","date":"2021-04-30","arxiv_id":"2105.00097","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 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; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/self-supervised-augmentation-consistency-for#ran","syntology_url":"https://syntology.ai/paper/2105.00097","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.00097"}},"official":{"repos":["visinf/da-sac"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/domain-adaptive-semantic-segmentation-with","slug":"domain-adaptive-semantic-segmentation-with","title":"Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation","date":"2021-04-28","arxiv_id":"2104.13613","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":3,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":3,"phrase":"3 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","sample_list":"/paper/domain-adaptive-semantic-segmentation-with#ran","syntology_url":"https://syntology.ai/paper/2104.13613","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.13613"}},"official":{"repos":["qinenergy/corda"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/adapting-imagenet-scale-models-to-complex","slug":"adapting-imagenet-scale-models-to-complex","title":"If your data distribution shifts, use self-learning","date":"2021-04-27","arxiv_id":"2104.12928","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 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; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/adapting-imagenet-scale-models-to-complex#ran","syntology_url":"https://syntology.ai/paper/2104.12928","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.12928"}},"official":{"repos":["bethgelab/robustness"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/semi-supervised-semantic-segmentation-with-2","slug":"semi-supervised-semantic-segmentation-with-2","title":"Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank","date":"2021-04-27","arxiv_id":"2104.13415","repositories_listed":1,"syntology":{"n":4,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":3,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 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; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/semi-supervised-semantic-segmentation-with-2#ran","syntology_url":"https://syntology.ai/paper/2104.13415","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.13415"}},"official":{"repos":["Shathe/SemiSeg-Contrastive"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/dannet-a-one-stage-domain-adaptation-network","slug":"dannet-a-one-stage-domain-adaptation-network","title":"DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation","date":"2021-04-22","arxiv_id":"2104.10834","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":2,"n_ran_checked":2,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"3 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/dannet-a-one-stage-domain-adaptation-network#ran","syntology_url":"https://syntology.ai/paper/2104.10834","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.10834"}},"official":{"repos":["W-zx-Y/DANNet"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/visualizing-adapted-knowledge-in-domain","slug":"visualizing-adapted-knowledge-in-domain","title":"Visualizing Adapted Knowledge in Domain Transfer","date":"2021-04-20","arxiv_id":"2104.10602","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":2,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":3,"phrase":"2 ran (of which 2 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; every one of the 2 samples that ran constructed an object rather than computing a result","sample_list":"/paper/visualizing-adapted-knowledge-in-domain#ran","syntology_url":"https://syntology.ai/paper/2104.10602","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.10602"}},"official":{"repos":["hou-yz/DA_visualization"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/semi-supervised-domain-adaptation-with-3","slug":"semi-supervised-domain-adaptation-with-3","title":"ECACL: A Holistic Framework for Semi-Supervised Domain Adaptation","date":"2021-04-19","arxiv_id":"2104.09136","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"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) · 1 unverified","sample_list":"/paper/semi-supervised-domain-adaptation-with-3#ran","syntology_url":"https://syntology.ai/paper/2104.09136","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.09136"}},"official":{"repos":["kailigo/pacl"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["unlocated"]}}},{"url":"/paper/cross-domain-adaptive-clustering-for-semi","slug":"cross-domain-adaptive-clustering-for-semi","title":"Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation","date":"2021-04-19","arxiv_id":"2104.09415","repositories_listed":3,"syntology":{"n":9,"n_ran":7,"n_constructed":0,"n_ran_checked":3,"n_instrument":4,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":2,"n_pointer_only":9,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 0 violated, 2 with no contract checked; 4 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/cross-domain-adaptive-clustering-for-semi#ran","syntology_url":"https://syntology.ai/paper/2104.09415","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.09415"}},"official":{"repos":["lijichang/CVPR2021-SSDA"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/tsdae-using-transformer-based-sequential","slug":"tsdae-using-transformer-based-sequential","title":"TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning","date":"2021-04-14","arxiv_id":"2104.06979","repositories_listed":6,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 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; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/tsdae-using-transformer-based-sequential#ran","syntology_url":"https://syntology.ai/paper/2104.06979","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.06979"}},"official":{"repos":["kwang2049/pytorch-bertflow","kwang2049/useb","ukplab/pytorch-bertflow"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/udalm-unsupervised-domain-adaptation-through","slug":"udalm-unsupervised-domain-adaptation-through","title":"UDALM: Unsupervised Domain Adaptation through Language Modeling","date":"2021-04-14","arxiv_id":"2104.07078","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/udalm-unsupervised-domain-adaptation-through#ran","syntology_url":"https://syntology.ai/paper/2104.07078","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.07078"}},"official":{"repos":["ckarouzos/slp_daptmlm"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/ovanet-one-vs-all-network-for-universal","slug":"ovanet-one-vs-all-network-for-universal","title":"OVANet: One-vs-All Network for Universal Domain Adaptation","date":"2021-04-07","arxiv_id":"2104.03344","repositories_listed":2,"syntology":{"n":12,"n_ran":9,"n_constructed":0,"n_ran_checked":7,"n_instrument":2,"n_unverified":3,"n_honours":0,"n_violates":1,"n_no_contract":6,"n_pointer_only":2,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 1 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/ovanet-one-vs-all-network-for-universal#ran","syntology_url":"https://syntology.ai/paper/2104.03344","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.03344"}},"official":{"repos":["VisionLearningGroup/OVANet"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":3,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/unsupervised-multi-source-domain-adaptation","slug":"unsupervised-multi-source-domain-adaptation","title":"Unsupervised Multi-source Domain Adaptation Without Access to Source Data","date":"2021-04-05","arxiv_id":"2104.01845","repositories_listed":1,"syntology":{"n":8,"n_ran":4,"n_constructed":3,"n_ran_checked":3,"n_instrument":1,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"4 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/unsupervised-multi-source-domain-adaptation#ran","syntology_url":"https://syntology.ai/paper/2104.01845","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.01845"}},"official":null}},{"url":"/paper/distill-and-fine-tune-effective-adaptation","slug":"distill-and-fine-tune-effective-adaptation","title":"DINE: Domain Adaptation from Single and Multiple Black-box Predictors","date":"2021-04-04","arxiv_id":"2104.01539","repositories_listed":3,"syntology":{"n":13,"n_ran":10,"n_constructed":0,"n_ran_checked":3,"n_instrument":7,"n_unverified":3,"n_honours":3,"n_violates":0,"n_no_contract":0,"n_pointer_only":10,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 3 honoured, 0 violated, 0 with no contract checked; 7 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/distill-and-fine-tune-effective-adaptation#ran","syntology_url":"https://syntology.ai/paper/2104.01539","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.01539"}},"official":{"repos":["tim-learn/Dis-tune","tim-learn/dine"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/unsupervised-domain-expansion-for-visual","slug":"unsupervised-domain-expansion-for-visual","title":"Unsupervised Domain Expansion for Visual Categorization","date":"2021-04-01","arxiv_id":"2104.00233","repositories_listed":2,"syntology":{"n":11,"n_ran":10,"n_constructed":0,"n_ran_checked":7,"n_instrument":3,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":1,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/unsupervised-domain-expansion-for-visual#ran","syntology_url":"https://syntology.ai/paper/2104.00233","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.00233"}},"official":{"repos":["li-xirong/ude"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/divergence-optimization-for-noisy-universal","slug":"divergence-optimization-for-noisy-universal","title":"Divergence Optimization for Noisy Universal Domain Adaptation","date":"2021-04-01","arxiv_id":"2104.00246","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":2,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":3,"phrase":"3 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/divergence-optimization-for-noisy-universal#ran","syntology_url":"https://syntology.ai/paper/2104.00246","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.00246"}},"official":null}},{"url":"/paper/curriculum-graph-co-teaching-for-multi-target","slug":"curriculum-graph-co-teaching-for-multi-target","title":"Curriculum Graph Co-Teaching for Multi-Target Domain Adaptation","date":"2021-04-01","arxiv_id":"2104.00808","repositories_listed":1,"syntology":{"n":6,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":6,"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) · 4 unverified","sample_list":"/paper/curriculum-graph-co-teaching-for-multi-target#ran","syntology_url":"https://syntology.ai/paper/2104.00808","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.00808"}},"official":{"repos":["Evgeneus/Graph-Domain-Adaptaion"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/geometric-unsupervised-domain-adaptation-for","slug":"geometric-unsupervised-domain-adaptation-for","title":"Geometric Unsupervised Domain Adaptation for Semantic Segmentation","date":"2021-03-30","arxiv_id":"2103.16694","repositories_listed":0,"syntology":{"n":14,"n_ran":14,"n_constructed":0,"n_ran_checked":14,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":14,"n_pointer_only":0,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 14 with no instrument failure: 0 honoured, 0 violated, 14 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/geometric-unsupervised-domain-adaptation-for#ran","syntology_url":"https://syntology.ai/paper/2103.16694","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.16694"}},"official":null}},{"url":"/paper/dynamic-domain-adaptation-for-efficient","slug":"dynamic-domain-adaptation-for-efficient","title":"Dynamic Domain Adaptation for Efficient Inference","date":"2021-03-26","arxiv_id":"2103.16403","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":2,"phrase":"1 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; 0 where Syntology's instrument failed) · 1 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/dynamic-domain-adaptation-for-efficient#ran","syntology_url":"https://syntology.ai/paper/2103.16403","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.16403"}},"official":{"repos":["BIT-DA/DDA"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/metaalign-coordinating-domain-alignment-and","slug":"metaalign-coordinating-domain-alignment-and","title":"MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation","date":"2021-03-25","arxiv_id":"2103.13575","repositories_listed":1,"syntology":{"n":12,"n_ran":5,"n_constructed":0,"n_ran_checked":2,"n_instrument":3,"n_unverified":7,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 3 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/metaalign-coordinating-domain-alignment-and#ran","syntology_url":"https://syntology.ai/paper/2103.13575","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.13575"}},"official":null}},{"url":"/paper/dranet-disentangling-representation-and","slug":"dranet-disentangling-representation-and","title":"DRANet: Disentangling Representation and Adaptation Networks for Unsupervised Cross-Domain Adaptation","date":"2021-03-24","arxiv_id":"2103.13447","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 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; 0 where Syntology's instrument failed) · 0 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/dranet-disentangling-representation-and#ran","syntology_url":"https://syntology.ai/paper/2103.13447","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.13447"}},"official":{"repos":["Seung-Hun-Lee/DRANet"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/transferable-semantic-augmentation-for-domain","slug":"transferable-semantic-augmentation-for-domain","title":"Transferable Semantic Augmentation for Domain Adaptation","date":"2021-03-23","arxiv_id":"2103.12562","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/transferable-semantic-augmentation-for-domain#ran","syntology_url":"https://syntology.ai/paper/2103.12562","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.12562"}},"official":{"repos":["BIT-DA/TSA"],"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"]}}},{"url":"/paper/cluster-contrast-for-unsupervised-person-re","slug":"cluster-contrast-for-unsupervised-person-re","title":"Cluster Contrast for Unsupervised Person Re-Identification","date":"2021-03-22","arxiv_id":"2103.11568","repositories_listed":4,"syntology":{"n":14,"n_ran":10,"n_constructed":0,"n_ran_checked":8,"n_instrument":2,"n_unverified":4,"n_honours":1,"n_violates":0,"n_no_contract":7,"n_pointer_only":5,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 1 honoured, 0 violated, 7 with no contract checked; 2 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/cluster-contrast-for-unsupervised-person-re#ran","syntology_url":"https://syntology.ai/paper/2103.11568","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.11568"}},"official":{"repos":["alibaba/cluster-contrast","wangguangyuan/ClusterContrast"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":4,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/dynamic-transfer-for-multi-source-domain","slug":"dynamic-transfer-for-multi-source-domain","title":"Dynamic Transfer for Multi-Source Domain Adaptation","date":"2021-03-19","arxiv_id":"2103.10583","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 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; 0 where Syntology's instrument failed) · 0 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/dynamic-transfer-for-multi-source-domain#ran","syntology_url":"https://syntology.ai/paper/2103.10583","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.10583"}},"official":{"repos":["liyunsheng13/DRT"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/optimizing-black-box-metrics-with-iterative","slug":"optimizing-black-box-metrics-with-iterative","title":"Optimizing Black-box Metrics with Iterative Example Weighting","date":"2021-02-18","arxiv_id":"2102.09492","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":2,"n_ran_checked":3,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":2,"n_pointer_only":4,"phrase":"4 ran (of which 2 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 1 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/optimizing-black-box-metrics-with-iterative#ran","syntology_url":"https://syntology.ai/paper/2102.09492","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2102.09492"}},"official":{"repos":["koyejolab/fweg"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":2,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/cross-domain-time-series-forecasting-with","slug":"cross-domain-time-series-forecasting-with","title":"Domain Adaptation for Time Series Forecasting via Attention Sharing","date":"2021-02-13","arxiv_id":"2102.06828","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":2,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":2,"phrase":"2 ran (of which 2 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) · 0 unverified; every one of the 2 samples that ran constructed an object rather than computing a result","sample_list":"/paper/cross-domain-time-series-forecasting-with#ran","syntology_url":"https://syntology.ai/paper/2102.06828","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2102.06828"}},"official":null}},{"url":"/paper/domain-adaptation-in-reinforcement-learning","slug":"domain-adaptation-in-reinforcement-learning","title":"Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation","date":"2021-02-10","arxiv_id":"2102.05714","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":3,"n_ran_checked":3,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":4,"phrase":"4 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/domain-adaptation-in-reinforcement-learning#ran","syntology_url":"https://syntology.ai/paper/2102.05714","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2102.05714"}},"official":{"repos":["KarlXing/LUSR"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/prototypical-pseudo-label-denoising-and","slug":"prototypical-pseudo-label-denoising-and","title":"Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation","date":"2021-01-26","arxiv_id":"2101.10979","repositories_listed":2,"syntology":{"n":17,"n_ran":8,"n_constructed":6,"n_ran_checked":6,"n_instrument":2,"n_unverified":9,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"8 ran (of which 6 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 9 unverified","sample_list":"/paper/prototypical-pseudo-label-denoising-and#ran","syntology_url":"https://syntology.ai/paper/2101.10979","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2101.10979"}},"official":{"repos":["microsoft/ProDA"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":6,"n_ran_no_instrument_failure":6,"n_unverified":9,"ran_from_kinds":["official"]}}},{"url":"/paper/1st-place-solution-to-visda-2020-bias","slug":"1st-place-solution-to-visda-2020-bias","title":"1st Place Solution to VisDA-2020: Bias Elimination for Domain Adaptive Pedestrian Re-identification","date":"2020-12-25","arxiv_id":"2012.13498","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 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; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/1st-place-solution-to-visda-2020-bias#ran","syntology_url":"https://syntology.ai/paper/2012.13498","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2012.13498"}},"official":{"repos":["vimar-gu/Bias-Eliminate-DA-ReID"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/joint-generative-and-contrastive-learning-for","slug":"joint-generative-and-contrastive-learning-for","title":"Joint Generative and Contrastive Learning for Unsupervised Person Re-identification","date":"2020-12-16","arxiv_id":"2012.09071","repositories_listed":2,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_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","sample_list":"/paper/joint-generative-and-contrastive-learning-for#ran","syntology_url":"https://syntology.ai/paper/2012.09071","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2012.09071"}},"official":{"repos":["chenhao2345/GCL"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["unlocated"]}}},{"url":"/paper/source-data-absent-unsupervised-domain","slug":"source-data-absent-unsupervised-domain","title":"Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer","date":"2020-12-14","arxiv_id":"2012.07297","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"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","sample_list":"/paper/source-data-absent-unsupervised-domain#ran","syntology_url":"https://syntology.ai/paper/2012.07297","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2012.07297"}},"official":{"repos":["tim-learn/SHOT-plus"],"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","unlocated"]}}},{"url":"/paper/aligning-hyperbolic-representations-an","slug":"aligning-hyperbolic-representations-an","title":"Aligning Hyperbolic Representations: an Optimal Transport-based approach","date":"2020-12-02","arxiv_id":"2012.01089","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/aligning-hyperbolic-representations-an#ran","syntology_url":"https://syntology.ai/paper/2012.01089","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2012.01089"}},"official":{"repos":["ahoyosid/hyperbolic_alignment"],"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"]}}},{"url":"/paper/pixel-level-cycle-association-a-new","slug":"pixel-level-cycle-association-a-new","title":"Pixel-Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation","date":"2020-10-31","arxiv_id":"2011.00147","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 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; 0 where Syntology's instrument failed) · 0 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/pixel-level-cycle-association-a-new#ran","syntology_url":"https://syntology.ai/paper/2011.00147","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2011.00147"}},"official":{"repos":["kgl-prml/Pixel-Level-Cycle-Association"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/cliniqg4qa-generating-diverse-questions-for","slug":"cliniqg4qa-generating-diverse-questions-for","title":"CliniQG4QA: Generating Diverse Questions for Domain Adaptation of Clinical Question Answering","date":"2020-10-30","arxiv_id":"2010.16021","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":1,"n_no_contract":0,"n_pointer_only":3,"phrase":"3 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; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/cliniqg4qa-generating-diverse-questions-for#ran","syntology_url":"https://syntology.ai/paper/2010.16021","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.16021"}},"official":{"repos":["panushri25/emrQA","sunlab-osu/CliniQG4QA"],"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","unlocated"]}}},{"url":"/paper/on-embodied-visual-navigation-in-real","slug":"on-embodied-visual-navigation-in-real","title":"On Embodied Visual Navigation in Real Environments Through Habitat","date":"2020-10-26","arxiv_id":"2010.13439","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 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; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/on-embodied-visual-navigation-in-real#ran","syntology_url":"https://syntology.ai/paper/2010.13439","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.13439"}},"official":{"repos":["rosanom/habitat-domain-adaptation"],"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"]}}},{"url":"/paper/gradient-flows-in-dataset-space","slug":"gradient-flows-in-dataset-space","title":"Dataset Dynamics via Gradient Flows in Probability Space","date":"2020-10-24","arxiv_id":"2010.12760","repositories_listed":1,"syntology":{"n":22,"n_ran":14,"n_constructed":0,"n_ran_checked":14,"n_instrument":0,"n_unverified":8,"n_honours":0,"n_violates":0,"n_no_contract":14,"n_pointer_only":0,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 14 with no instrument failure: 0 honoured, 0 violated, 14 with no contract checked; 0 where Syntology's instrument failed) · 8 unverified","sample_list":"/paper/gradient-flows-in-dataset-space#ran","syntology_url":"https://syntology.ai/paper/2010.12760","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.12760"}},"official":null}},{"url":"/paper/active-domain-adaptation-via-clustering","slug":"active-domain-adaptation-via-clustering","title":"Active Domain Adaptation via Clustering Uncertainty-weighted Embeddings","date":"2020-10-16","arxiv_id":"2010.08666","repositories_listed":1,"syntology":{"n":10,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"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) · 3 unverified","sample_list":"/paper/active-domain-adaptation-via-clustering#ran","syntology_url":"https://syntology.ai/paper/2010.08666","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.08666"}},"official":{"repos":["virajprabhu/clue"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/adaptive-attentive-geolocalization-from-few","slug":"adaptive-attentive-geolocalization-from-few","title":"Adaptive-Attentive Geolocalization from few queries: a hybrid approach","date":"2020-10-14","arxiv_id":"2010.06897","repositories_listed":2,"syntology":{"n":8,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":1,"phrase":"5 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; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/adaptive-attentive-geolocalization-from-few#ran","syntology_url":"https://syntology.ai/paper/2010.06897","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.06897"}},"official":{"repos":["valeriopaolicelli/AdAGeo","valeriopaolicelli/adageo-WACV2021"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/robust-optimal-transport-with-applications-in","slug":"robust-optimal-transport-with-applications-in","title":"Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation","date":"2020-10-12","arxiv_id":"2010.05862","repositories_listed":2,"syntology":{"n":6,"n_ran":3,"n_constructed":1,"n_ran_checked":2,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":6,"phrase":"3 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; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/robust-optimal-transport-with-applications-in#ran","syntology_url":"https://syntology.ai/paper/2010.05862","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.05862"}},"official":{"repos":["yogeshbalaji/robustOT"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/permuted-adain-enhancing-the-representation","slug":"permuted-adain-enhancing-the-representation","title":"Permuted AdaIN: Reducing the Bias Towards Global Statistics in Image Classification","date":"2020-10-09","arxiv_id":"2010.05785","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_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) · 0 unverified","sample_list":"/paper/permuted-adain-enhancing-the-representation#ran","syntology_url":"https://syntology.ai/paper/2010.05785","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.05785"}},"official":{"repos":["onuriel/PermutedAdaIN"],"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"]}}},{"url":"/paper/covariate-shift-adaptation-in-high","slug":"covariate-shift-adaptation-in-high","title":"Effective Sample Size, Dimensionality, and Generalization in Covariate Shift Adaptation","date":"2020-10-02","arxiv_id":"2010.01184","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 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; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/covariate-shift-adaptation-in-high#ran","syntology_url":"https://syntology.ai/paper/2010.01184","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.01184"}},"official":{"repos":["felipemaiapolo/infoselect"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/unsupervised-model-adaptation-for-continual","slug":"unsupervised-model-adaptation-for-continual","title":"Unsupervised Model Adaptation for Continual Semantic Segmentation","date":"2020-09-26","arxiv_id":"2009.12518","repositories_listed":1,"syntology":{"n":13,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/unsupervised-model-adaptation-for-continual#ran","syntology_url":"https://syntology.ai/paper/2009.12518","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2009.12518"}},"official":null}},{"url":"/paper/adapting-bert-for-word-sense-disambiguation","slug":"adapting-bert-for-word-sense-disambiguation","title":"Adapting BERT for Word Sense Disambiguation with Gloss Selection Objective and Example Sentences","date":"2020-09-24","arxiv_id":"2009.11795","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"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) · 1 unverified","sample_list":"/paper/adapting-bert-for-word-sense-disambiguation#ran","syntology_url":"https://syntology.ai/paper/2009.11795","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2009.11795"}},"official":{"repos":["BPYap/BERT-WSD"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/collaborative-training-between-region-1","slug":"collaborative-training-between-region-1","title":"Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection","date":"2020-09-17","arxiv_id":"2009.08119","repositories_listed":1,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/collaborative-training-between-region-1#ran","syntology_url":"https://syntology.ai/paper/2009.08119","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2009.08119"}},"official":{"repos":["GanlongZhao/CST_DA_detection"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/the-unbalanced-gromov-wasserstein-distance","slug":"the-unbalanced-gromov-wasserstein-distance","title":"The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation","date":"2020-09-09","arxiv_id":"2009.04266","repositories_listed":2,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 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; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/the-unbalanced-gromov-wasserstein-distance#ran","syntology_url":"https://syntology.ai/paper/2009.04266","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2009.04266"}},"official":{"repos":["thibsej/unbalanced_gromov_wasserstein"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/learning-from-a-complementary-label-source","slug":"learning-from-a-complementary-label-source","title":"Learning from a Complementary-label Source Domain: Theory and Algorithms","date":"2020-08-04","arxiv_id":"2008.01454","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":4,"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) · 1 unverified","sample_list":"/paper/learning-from-a-complementary-label-source#ran","syntology_url":"https://syntology.ai/paper/2008.01454","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2008.01454"}},"official":{"repos":["Yiyang98/BFUDA"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/adversarial-bipartite-graph-learning-for","slug":"adversarial-bipartite-graph-learning-for","title":"Adversarial Bipartite Graph Learning for Video Domain Adaptation","date":"2020-07-31","arxiv_id":"2007.15829","repositories_listed":1,"syntology":{"n":9,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 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; 0 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/adversarial-bipartite-graph-learning-for#ran","syntology_url":"https://syntology.ai/paper/2007.15829","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.15829"}},"official":{"repos":["Luoyadan/MM2020_ABG"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/clarinet-a-one-step-approach-towards-budget","slug":"clarinet-a-one-step-approach-towards-budget","title":"Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation","date":"2020-07-29","arxiv_id":"2007.14612","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":4,"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) · 1 unverified","sample_list":"/paper/clarinet-a-one-step-approach-towards-budget#ran","syntology_url":"https://syntology.ai/paper/2007.14612","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.14612"}},"official":{"repos":["Yiyang98/BFUDA"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/unsupervised-domain-adaptation-in-the","slug":"unsupervised-domain-adaptation-in-the","title":"Unsupervised Domain Adaptation in the Dissimilarity Space for Person Re-identification","date":"2020-07-27","arxiv_id":"2007.13890","repositories_listed":2,"syntology":{"n":19,"n_ran":11,"n_constructed":0,"n_ran_checked":9,"n_instrument":2,"n_unverified":8,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":3,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 2 where Syntology's instrument failed) · 8 unverified","sample_list":"/paper/unsupervised-domain-adaptation-in-the#ran","syntology_url":"https://syntology.ai/paper/2007.13890","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.13890"}},"official":{"repos":["djidje/D-MMD"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/dacs-domain-adaptation-via-cross-domain-mixed","slug":"dacs-domain-adaptation-via-cross-domain-mixed","title":"DACS: Domain Adaptation via Cross-domain Mixed Sampling","date":"2020-07-17","arxiv_id":"2007.08702","repositories_listed":2,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":1,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/dacs-domain-adaptation-via-cross-domain-mixed#ran","syntology_url":"https://syntology.ai/paper/2007.08702","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.08702"}},"official":{"repos":["vikolss/DACS"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["unlocated"]}}},{"url":"/paper/label-propagation-with-augmented-anchors-a","slug":"label-propagation-with-augmented-anchors-a","title":"Label Propagation with Augmented Anchors: A Simple Semi-Supervised Learning baseline for Unsupervised Domain Adaptation","date":"2020-07-15","arxiv_id":"2007.07695","repositories_listed":1,"syntology":{"n":9,"n_ran":9,"n_constructed":0,"n_ran_checked":8,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":1,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/label-propagation-with-augmented-anchors-a#ran","syntology_url":"https://syntology.ai/paper/2007.07695","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.07695"}},"official":{"repos":["YBZh/Label-Propagation-with-Augmented-Anchors"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/automated-synthetic-to-real-generalization","slug":"automated-synthetic-to-real-generalization","title":"Automated Synthetic-to-Real Generalization","date":"2020-07-14","arxiv_id":"2007.06965","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_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","sample_list":"/paper/automated-synthetic-to-real-generalization#ran","syntology_url":"https://syntology.ai/paper/2007.06965","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.06965"}},"official":{"repos":["NVlabs/ASG"],"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"]}}},{"url":"/paper/combating-domain-shift-with-self-taught","slug":"combating-domain-shift-with-self-taught","title":"Domain Adaptation with Auxiliary Target Domain-Oriented Classifier","date":"2020-07-08","arxiv_id":"2007.04171","repositories_listed":2,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_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","sample_list":"/paper/combating-domain-shift-with-self-taught#ran","syntology_url":"https://syntology.ai/paper/2007.04171","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.04171"}},"official":{"repos":["tim-learn/atdoc"],"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"]}}},{"url":"/paper/cycle-starnet-bridging-the-gap-between-theory","slug":"cycle-starnet-bridging-the-gap-between-theory","title":"Cycle-StarNet: Bridging the gap between theory and data by leveraging large datasets","date":"2020-07-06","arxiv_id":"2007.03109","repositories_listed":1,"syntology":{"n":9,"n_ran":6,"n_constructed":1,"n_ran_checked":2,"n_instrument":4,"n_unverified":3,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":9,"phrase":"6 ran (of which 1 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 4 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/cycle-starnet-bridging-the-gap-between-theory#ran","syntology_url":"https://syntology.ai/paper/2007.03109","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.03109"}},"official":{"repos":["teaghan/Cycle_SN"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":1,"n_ran_no_instrument_failure":2,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/estimating-generalization-under-distribution","slug":"estimating-generalization-under-distribution","title":"Estimating Generalization under Distribution Shifts via Domain-Invariant Representations","date":"2020-07-06","arxiv_id":"2007.03511","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_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","sample_list":"/paper/estimating-generalization-under-distribution#ran","syntology_url":"https://syntology.ai/paper/2007.03511","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.03511"}},"official":{"repos":["chingyaoc/estimating-generalization"],"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"]}}},{"url":"/paper/off-dynamics-reinforcement-learning-training","slug":"off-dynamics-reinforcement-learning-training","title":"Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers","date":"2020-06-24","arxiv_id":"2006.13916","repositories_listed":2,"syntology":{"n":23,"n_ran":21,"n_constructed":4,"n_ran_checked":15,"n_instrument":6,"n_unverified":2,"n_honours":3,"n_violates":0,"n_no_contract":12,"n_pointer_only":7,"phrase":"21 ran (of which 4 constructed an object rather than computing a result; 15 with no instrument failure: 3 honoured, 0 violated, 12 with no contract checked; 6 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/off-dynamics-reinforcement-learning-training#ran","syntology_url":"https://syntology.ai/paper/2006.13916","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.13916"}},"official":null}},{"url":"/paper/rescaling-egocentric-vision","slug":"rescaling-egocentric-vision","title":"Rescaling Egocentric Vision","date":"2020-06-23","arxiv_id":"2006.13256","repositories_listed":7,"syntology":{"n":18,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":8,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 8 unverified","sample_list":"/paper/rescaling-egocentric-vision#ran","syntology_url":"https://syntology.ai/paper/2006.13256","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.13256"}},"official":{"repos":["epic-kitchens/epic-kitchens-100-narrator","epic-kitchens/epic-kitchens-100-annotations"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/club-a-contrastive-log-ratio-upper-bound-of","slug":"club-a-contrastive-log-ratio-upper-bound-of","title":"CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information","date":"2020-06-22","arxiv_id":"2006.12013","repositories_listed":2,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_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","sample_list":"/paper/club-a-contrastive-log-ratio-upper-bound-of#ran","syntology_url":"https://syntology.ai/paper/2006.12013","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.12013"}},"official":{"repos":["Linear95/CLUB"],"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"]}}},{"url":"/paper/progressive-graph-learning-for-open-set","slug":"progressive-graph-learning-for-open-set","title":"Progressive Graph Learning for Open-Set Domain Adaptation","date":"2020-06-22","arxiv_id":"2006.12087","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 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; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/progressive-graph-learning-for-open-set#ran","syntology_url":"https://syntology.ai/paper/2006.12087","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.12087"}},"official":{"repos":["BUserName/PGL"],"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"]}}},{"url":"/paper/fully-test-time-adaptation-by-entropy","slug":"fully-test-time-adaptation-by-entropy","title":"Tent: Fully Test-time Adaptation by Entropy Minimization","date":"2020-06-18","arxiv_id":"2006.10726","repositories_listed":2,"syntology":{"n":9,"n_ran":8,"n_constructed":2,"n_ran_checked":2,"n_instrument":6,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":3,"phrase":"8 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 6 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/fully-test-time-adaptation-by-entropy#ran","syntology_url":"https://syntology.ai/paper/2006.10726","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.10726"}},"official":{"repos":["DequanWang/tent"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/non-negative-bregman-divergence-minimization","slug":"non-negative-bregman-divergence-minimization","title":"Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation","date":"2020-06-12","arxiv_id":"2006.06979","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_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) · 1 unverified","sample_list":"/paper/non-negative-bregman-divergence-minimization#ran","syntology_url":"https://syntology.ai/paper/2006.06979","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.06979"}},"official":{"repos":["MasaKat0/D3RE"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/attentive-waveblock-complementarity-enhanced","slug":"attentive-waveblock-complementarity-enhanced","title":"Attentive WaveBlock: Complementarity-enhanced Mutual Networks for Unsupervised Domain Adaptation in Person Re-identification and Beyond","date":"2020-06-11","arxiv_id":"2006.06525","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"3 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; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/attentive-waveblock-complementarity-enhanced#ran","syntology_url":"https://syntology.ai/paper/2006.06525","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.06525"}},"official":{"repos":["WangWenhao0716/Attentive-WaveBlock"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/self-paced-contrastive-learning-with-hybrid","slug":"self-paced-contrastive-learning-with-hybrid","title":"Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID","date":"2020-06-04","arxiv_id":"2006.02713","repositories_listed":3,"syntology":{"n":5,"n_ran":3,"n_constructed":2,"n_ran_checked":2,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"3 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/self-paced-contrastive-learning-with-hybrid#ran","syntology_url":"https://syntology.ai/paper/2006.02713","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.02713"}},"official":{"repos":["yxgeee/SpCL"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/language-models-are-few-shot-learners","slug":"language-models-are-few-shot-learners","title":"Language Models are Few-Shot Learners","date":"2020-05-28","arxiv_id":"2005.14165","repositories_listed":67,"syntology":{"n":65,"n_ran":45,"n_constructed":0,"n_ran_checked":40,"n_instrument":5,"n_unverified":20,"n_honours":2,"n_violates":1,"n_no_contract":37,"n_pointer_only":7,"phrase":"45 ran (of which 0 constructed an object rather than computing a result; 40 with no instrument failure: 2 honoured, 1 violated, 37 with no contract checked; 5 where Syntology's instrument failed) · 20 unverified","sample_list":"/paper/language-models-are-few-shot-learners#ran","syntology_url":"https://syntology.ai/paper/2005.14165","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.14165"}},"official":{"repos":["openai/gpt-3"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/multi-source-deep-domain-adaptation-with-weak","slug":"multi-source-deep-domain-adaptation-with-weak","title":"Multi-Source Deep Domain Adaptation with Weak Supervision for Time-Series Sensor Data","date":"2020-05-22","arxiv_id":"2005.10996","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"3 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; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/multi-source-deep-domain-adaptation-with-weak#ran","syntology_url":"https://syntology.ai/paper/2005.10996","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.10996"}},"official":{"repos":["floft/codats"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/esam-discriminative-domain-adaptation-with","slug":"esam-discriminative-domain-adaptation-with","title":"ESAM: Discriminative Domain Adaptation with Non-Displayed Items to Improve Long-Tail Performance","date":"2020-05-21","arxiv_id":"2005.10545","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_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","sample_list":"/paper/esam-discriminative-domain-adaptation-with#ran","syntology_url":"https://syntology.ai/paper/2005.10545","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.10545"}},"official":{"repos":["A-bone1/ESAM"],"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"]}}},{"url":"/paper/unsupervised-instance-segmentation-in","slug":"unsupervised-instance-segmentation-in","title":"Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weighting","date":"2020-05-05","arxiv_id":"2005.02066","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 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; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/unsupervised-instance-segmentation-in#ran","syntology_url":"https://syntology.ai/paper/2005.02066","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.02066"}},"official":{"repos":["dliu5812/PDAM"],"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"]}}},{"url":"/paper/towards-accurate-and-robust-domain-adaptation","slug":"towards-accurate-and-robust-domain-adaptation","title":"Towards Accurate and Robust Domain Adaptation under Noisy Environments","date":"2020-04-27","arxiv_id":"2004.12529","repositories_listed":1,"syntology":{"n":6,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":3,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_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) · 3 unverified","sample_list":"/paper/towards-accurate-and-robust-domain-adaptation#ran","syntology_url":"https://syntology.ai/paper/2004.12529","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.12529"}},"official":{"repos":["zhyhan/RDA"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/maximum-density-divergence-for-domain","slug":"maximum-density-divergence-for-domain","title":"Maximum Density Divergence for Domain Adaptation","date":"2020-04-27","arxiv_id":"2004.12615","repositories_listed":2,"syntology":{"n":4,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 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; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/maximum-density-divergence-for-domain#ran","syntology_url":"https://syntology.ai/paper/2004.12615","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.12615"}},"official":{"repos":["lijin118/ATM"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/federated-transfer-learning-for-eeg-signal","slug":"federated-transfer-learning-for-eeg-signal","title":"Federated Transfer Learning for EEG Signal Classification","date":"2020-04-26","arxiv_id":"2004.12321","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":2,"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) · 1 unverified","sample_list":"/paper/federated-transfer-learning-for-eeg-signal#ran","syntology_url":"https://syntology.ai/paper/2004.12321","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.12321"}},"official":{"repos":["DashanGao/Federated-Transfer-Learning-for-EEG"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/unsupervised-domain-adaptation-through-inter","slug":"unsupervised-domain-adaptation-through-inter","title":"Unsupervised Domain Adaptation through Inter-modal Rotation for RGB-D Object Recognition","date":"2020-04-21","arxiv_id":"2004.10016","repositories_listed":3,"syntology":{"n":10,"n_ran":9,"n_constructed":0,"n_ran_checked":7,"n_instrument":2,"n_unverified":1,"n_honours":1,"n_violates":1,"n_no_contract":5,"n_pointer_only":5,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 1 honoured, 1 violated, 5 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/unsupervised-domain-adaptation-through-inter#ran","syntology_url":"https://syntology.ai/paper/2004.10016","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.10016"}},"official":null}},{"url":"/paper/unsupervised-intra-domain-adaptation-for","slug":"unsupervised-intra-domain-adaptation-for","title":"Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision","date":"2020-04-16","arxiv_id":"2004.07703","repositories_listed":2,"syntology":{"n":8,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":2,"phrase":"5 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; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/unsupervised-intra-domain-adaptation-for#ran","syntology_url":"https://syntology.ai/paper/2004.07703","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.07703"}},"official":{"repos":["feipan664/IntraDA"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/adversarial-style-mining-for-one-shot","slug":"adversarial-style-mining-for-one-shot","title":"Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation","date":"2020-04-13","arxiv_id":"2004.06042","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":0,"n_honours":3,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 3 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/adversarial-style-mining-for-one-shot#ran","syntology_url":"https://syntology.ai/paper/2004.06042","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.06042"}},"official":{"repos":["RoyalVane/ASM"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/fda-fourier-domain-adaptation-for-semantic","slug":"fda-fourier-domain-adaptation-for-semantic","title":"FDA: Fourier Domain Adaptation for Semantic Segmentation","date":"2020-04-11","arxiv_id":"2004.05498","repositories_listed":3,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":3,"phrase":"2 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; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/fda-fourier-domain-adaptation-for-semantic#ran","syntology_url":"https://syntology.ai/paper/2004.05498","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.05498"}},"official":{"repos":["YanchaoYang/FDA"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/kdconv-a-chinese-multi-domain-dialogue","slug":"kdconv-a-chinese-multi-domain-dialogue","title":"KdConv: A Chinese Multi-domain Dialogue Dataset Towards Multi-turn Knowledge-driven Conversation","date":"2020-04-08","arxiv_id":"2004.04100","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/kdconv-a-chinese-multi-domain-dialogue#ran","syntology_url":"https://syntology.ai/paper/2004.04100","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.04100"}},"official":{"repos":["thu-coai/KdConv"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/gradually-vanishing-bridge-for-adversarial","slug":"gradually-vanishing-bridge-for-adversarial","title":"Gradually Vanishing Bridge for Adversarial Domain Adaptation","date":"2020-03-30","arxiv_id":"2003.13183","repositories_listed":2,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_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) · 1 unverified","sample_list":"/paper/gradually-vanishing-bridge-for-adversarial#ran","syntology_url":"https://syntology.ai/paper/2003.13183","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.13183"}},"official":{"repos":["cuishuhao/GVB"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/self-supervised-learning-for-domain","slug":"self-supervised-learning-for-domain","title":"Self-Supervised Learning for Domain Adaptation on Point-Clouds","date":"2020-03-29","arxiv_id":"2003.12641","repositories_listed":3,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"1 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; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/self-supervised-learning-for-domain#ran","syntology_url":"https://syntology.ai/paper/2003.12641","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.12641"}},"official":{"repos":["IdanAchituve/DefRec_and_PCM","idanachi/DefRec_and_PCM"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/towards-discriminability-and-diversity-batch","slug":"towards-discriminability-and-diversity-batch","title":"Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations","date":"2020-03-27","arxiv_id":"2003.12237","repositories_listed":2,"syntology":{"n":4,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":2,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/towards-discriminability-and-diversity-batch#ran","syntology_url":"https://syntology.ai/paper/2003.12237","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.12237"}},"official":{"repos":["cuishuhao/BNM"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/rethinking-class-balanced-methods-for-long","slug":"rethinking-class-balanced-methods-for-long","title":"Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective","date":"2020-03-24","arxiv_id":"2003.10780","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/rethinking-class-balanced-methods-for-long#ran","syntology_url":"https://syntology.ai/paper/2003.10780","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.10780"}},"official":{"repos":["abdullahjamal/Longtail_DA"],"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":["official"]}}},{"url":"/paper/scrabblegan-semi-supervised-varying-length","slug":"scrabblegan-semi-supervised-varying-length","title":"ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation","date":"2020-03-23","arxiv_id":"2003.10557","repositories_listed":3,"syntology":{"n":15,"n_ran":14,"n_constructed":0,"n_ran_checked":12,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":12,"n_pointer_only":3,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/scrabblegan-semi-supervised-varying-length#ran","syntology_url":"https://syntology.ai/paper/2003.10557","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.10557"}},"official":null}},{"url":"/paper/unsupervised-domain-adaptation-via-4","slug":"unsupervised-domain-adaptation-via-4","title":"Unsupervised Domain Adaptation via Structurally Regularized Deep Clustering","date":"2020-03-19","arxiv_id":"2003.08607","repositories_listed":2,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":2,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/unsupervised-domain-adaptation-via-4#ran","syntology_url":"https://syntology.ai/paper/2003.08607","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.08607"}},"official":{"repos":["huitangtang/SRDC-CVPR2020"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/differential-treatment-for-stuff-and-things-a","slug":"differential-treatment-for-stuff-and-things-a","title":"Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation","date":"2020-03-18","arxiv_id":"2003.08040","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/differential-treatment-for-stuff-and-things-a#ran","syntology_url":"https://syntology.ai/paper/2003.08040","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.08040"}},"official":{"repos":["SHI-Labs/Unsupervised-Domain-Adaptation-with-Differential-Treatment"],"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"]}}},{"url":"/paper/unified-image-and-video-saliency-modeling","slug":"unified-image-and-video-saliency-modeling","title":"Unified Image and Video Saliency Modeling","date":"2020-03-11","arxiv_id":"2003.05477","repositories_listed":2,"syntology":{"n":9,"n_ran":7,"n_constructed":0,"n_ran_checked":5,"n_instrument":2,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":4,"n_pointer_only":1,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 0 violated, 4 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/unified-image-and-video-saliency-modeling#ran","syntology_url":"https://syntology.ai/paper/2003.05477","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.05477"}},"official":{"repos":["rdroste/unisal"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/domain-adaptation-with-conditional","slug":"domain-adaptation-with-conditional","title":"Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift","date":"2020-03-10","arxiv_id":"2003.04475","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":1,"n_ran_checked":1,"n_instrument":3,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"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) · 2 unverified","sample_list":"/paper/domain-adaptation-with-conditional#ran","syntology_url":"https://syntology.ai/paper/2003.04475","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.04475"}},"official":null}}],"record_sha256":"8fefd00b838c574c6abac819aacfc8dfdbc25acf08c79cbf508f73b502d238f3","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}