{"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/representation-learning/papers/ran/10","list_of":"/task/representation-learning","task":"Representation Learning","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":10,"pages_in_order":15,"rows_per_page":100,"rows":[901,1000],"of":1439,"counts":{"archive_papers_tagged":10580,"with_a_code_link":4662,"where_syntology_ran_a_sample":1439,"not_listed_spam_title":0,"listed":10580,"listed_where_code_ran":1439,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1228,"every_run_a_failure_of_syntologys_instrument":211,"listed_with_a_run_with_no_instrument_failure":1228,"listed_every_run_a_failure_of_syntologys_instrument":211,"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/representation-learning/papers/ran/1","prev":"/task/representation-learning/papers/ran/9","next":"/task/representation-learning/papers/ran/11","papers":[{"url":"/paper/constrained-mean-shift-using-distant-yet","slug":"constrained-mean-shift-using-distant-yet","title":"Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning","date":"2021-12-08","arxiv_id":"2112.04607","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":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/constrained-mean-shift-using-distant-yet#ran","syntology_url":"https://syntology.ai/paper/2112.04607","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.04607"}},"official":{"repos":["ucdvision/cmsf"],"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/unsupervised-representation-learning-via","slug":"unsupervised-representation-learning-via","title":"Unsupervised Representation Learning via Neural Activation Coding","date":"2021-12-07","arxiv_id":"2112.04014","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/unsupervised-representation-learning-via#ran","syntology_url":"https://syntology.ai/paper/2112.04014","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.04014"}},"official":{"repos":["yookoon/nac"],"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/joint-learning-of-localized-representations","slug":"joint-learning-of-localized-representations","title":"Joint Learning of Localized Representations from Medical Images and Reports","date":"2021-12-06","arxiv_id":"2112.02889","repositories_listed":1,"syntology":{"n":7,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":6,"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) · 6 unverified","sample_list":"/paper/joint-learning-of-localized-representations#ran","syntology_url":"https://syntology.ai/paper/2112.02889","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.02889"}},"official":{"repos":["philip-mueller/lovt"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/general-facial-representation-learning-in-a","slug":"general-facial-representation-learning-in-a","title":"General Facial Representation Learning in a Visual-Linguistic Manner","date":"2021-12-06","arxiv_id":"2112.03109","repositories_listed":2,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":3,"n_pointer_only":4,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 1 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/general-facial-representation-learning-in-a#ran","syntology_url":"https://syntology.ai/paper/2112.03109","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.03109"}},"official":{"repos":["FacePerceiver/FaRL"],"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":["listed","official"]}}},{"url":"/paper/swintrack-a-simple-and-strong-baseline-for","slug":"swintrack-a-simple-and-strong-baseline-for","title":"SwinTrack: A Simple and Strong Baseline for Transformer Tracking","date":"2021-12-02","arxiv_id":"2112.00995","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":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) · 1 unverified","sample_list":"/paper/swintrack-a-simple-and-strong-baseline-for#ran","syntology_url":"https://syntology.ai/paper/2112.00995","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.00995"}},"official":{"repos":["litinglin/swintrack"],"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/iterative-frame-level-representation-learning","slug":"iterative-frame-level-representation-learning","title":"Iterative Contrast-Classify For Semi-supervised Temporal Action Segmentation","date":"2021-12-02","arxiv_id":"2112.01402","repositories_listed":1,"syntology":{"n":10,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":4,"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) · 4 unverified","sample_list":"/paper/iterative-frame-level-representation-learning#ran","syntology_url":"https://syntology.ai/paper/2112.01402","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.01402"}},"official":{"repos":["dipika-singhania/ICC-Semi-Supervised-TAS"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/molecular-contrastive-learning-with-chemical","slug":"molecular-contrastive-learning-with-chemical","title":"Molecular Contrastive Learning with Chemical Element Knowledge Graph","date":"2021-12-01","arxiv_id":"2112.00544","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/molecular-contrastive-learning-with-chemical#ran","syntology_url":"https://syntology.ai/paper/2112.00544","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.00544"}},"official":{"repos":["ZJU-Fangyin/KCL"],"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/diffusion-autoencoders-toward-a-meaningful","slug":"diffusion-autoencoders-toward-a-meaningful","title":"Diffusion Autoencoders: Toward a Meaningful and Decodable Representation","date":"2021-11-30","arxiv_id":"2111.15640","repositories_listed":3,"syntology":{"n":15,"n_ran":13,"n_constructed":0,"n_ran_checked":13,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":13,"n_pointer_only":2,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 13 with no instrument failure: 0 honoured, 0 violated, 13 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/diffusion-autoencoders-toward-a-meaningful#ran","syntology_url":"https://syntology.ai/paper/2111.15640","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.15640"}},"official":{"repos":["phizaz/diffae"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":13,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/on-the-integration-of-self-attention-and","slug":"on-the-integration-of-self-attention-and","title":"On the Integration of Self-Attention and Convolution","date":"2021-11-29","arxiv_id":"2111.14556","repositories_listed":2,"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/on-the-integration-of-self-attention-and#ran","syntology_url":"https://syntology.ai/paper/2111.14556","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.14556"}},"official":{"repos":["leaplabthu/acmix"],"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/latent-space-smoothing-for-individually-fair-1","slug":"latent-space-smoothing-for-individually-fair-1","title":"Latent Space Smoothing for Individually Fair Representations","date":"2021-11-26","arxiv_id":"2111.13650","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/latent-space-smoothing-for-individually-fair-1#ran","syntology_url":"https://syntology.ai/paper/2111.13650","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.13650"}},"official":{"repos":["eth-sri/lassi"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/failure-modes-of-domain-generalization","slug":"failure-modes-of-domain-generalization","title":"Failure Modes of Domain Generalization Algorithms","date":"2021-11-26","arxiv_id":"2111.13733","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/failure-modes-of-domain-generalization#ran","syntology_url":"https://syntology.ai/paper/2111.13733","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.13733"}},"official":{"repos":["tigrangalstyan/wilds"],"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/representation-learning-of-logic-circuits","slug":"representation-learning-of-logic-circuits","title":"DeepGate: Learning Neural Representations of Logic Gates","date":"2021-11-26","arxiv_id":"2111.14616","repositories_listed":1,"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":3,"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/representation-learning-of-logic-circuits#ran","syntology_url":"https://syntology.ai/paper/2111.14616","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.14616"}},"official":{"repos":["cure-lab/DeepGate"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/self-distilled-self-supervised-representation","slug":"self-distilled-self-supervised-representation","title":"Self-Distilled Self-Supervised Representation Learning","date":"2021-11-25","arxiv_id":"2111.12958","repositories_listed":1,"syntology":{"n":11,"n_ran":8,"n_constructed":0,"n_ran_checked":6,"n_instrument":2,"n_unverified":3,"n_honours":1,"n_violates":1,"n_no_contract":4,"n_pointer_only":3,"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) · 3 unverified","sample_list":"/paper/self-distilled-self-supervised-representation#ran","syntology_url":"https://syntology.ai/paper/2111.12958","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.12958"}},"official":{"repos":["hagiss/sdssl"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/morphmlp-a-self-attention-free-mlp-like","slug":"morphmlp-a-self-attention-free-mlp-like","title":"MorphMLP: An Efficient MLP-Like Backbone for Spatial-Temporal Representation Learning","date":"2021-11-24","arxiv_id":"2111.12527","repositories_listed":2,"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/morphmlp-a-self-attention-free-mlp-like#ran","syntology_url":"https://syntology.ai/paper/2111.12527","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.12527"}},"official":{"repos":["MTLab/MorphMLP"],"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/why-do-self-supervised-models-transfer","slug":"why-do-self-supervised-models-transfer","title":"Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks","date":"2021-11-22","arxiv_id":"2111.11398","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/why-do-self-supervised-models-transfer#ran","syntology_url":"https://syntology.ai/paper/2111.11398","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.11398"}},"official":{"repos":["linusericsson/ssl-invariances"],"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/improving-transferability-of-representations","slug":"improving-transferability-of-representations","title":"Improving Transferability of Representations via Augmentation-Aware Self-Supervision","date":"2021-11-18","arxiv_id":"2111.09613","repositories_listed":2,"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/improving-transferability-of-representations#ran","syntology_url":"https://syntology.ai/paper/2111.09613","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.09613"}},"official":{"repos":["hankook/augself"],"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/simmim-a-simple-framework-for-masked-image","slug":"simmim-a-simple-framework-for-masked-image","title":"SimMIM: A Simple Framework for Masked Image Modeling","date":"2021-11-18","arxiv_id":"2111.09886","repositories_listed":7,"syntology":{"n":14,"n_ran":9,"n_constructed":7,"n_ran_checked":8,"n_instrument":1,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":0,"phrase":"9 ran (of which 7 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) · 5 unverified","sample_list":"/paper/simmim-a-simple-framework-for-masked-image#ran","syntology_url":"https://syntology.ai/paper/2111.09886","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.09886"}},"official":{"repos":["microsoft/simmim"],"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":["listed","official"]}}},{"url":"/paper/unifying-heterogenous-electronic-health-1","slug":"unifying-heterogenous-electronic-health-1","title":"Unifying Heterogeneous Electronic Health Records Systems via Text-Based Code Embedding","date":"2021-11-12","arxiv_id":"2111.09098","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":1,"n_ran_checked":1,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"2 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; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/unifying-heterogenous-electronic-health-1#ran","syntology_url":"https://syntology.ai/paper/2111.09098","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.09098"}},"official":{"repos":["hoon9405/DescEmb"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/rave-a-variational-autoencoder-for-fast-and-1","slug":"rave-a-variational-autoencoder-for-fast-and-1","title":"RAVE: A variational autoencoder for fast and high-quality neural audio synthesis","date":"2021-11-09","arxiv_id":"2111.05011","repositories_listed":3,"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":1,"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/rave-a-variational-autoencoder-for-fast-and-1#ran","syntology_url":"https://syntology.ai/paper/2111.05011","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.05011"}},"official":{"repos":["caillonantoine/RAVE"],"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/generalized-radiograph-representation","slug":"generalized-radiograph-representation","title":"Generalized Radiograph Representation Learning via Cross-supervision between Images and Free-text Radiology Reports","date":"2021-11-04","arxiv_id":"2111.03452","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/generalized-radiograph-representation#ran","syntology_url":"https://syntology.ai/paper/2111.03452","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.03452"}},"official":{"repos":["funnyzhou/refers"],"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/a-comparison-of-discrete-and-soft-speech","slug":"a-comparison-of-discrete-and-soft-speech","title":"A Comparison of Discrete and Soft Speech Units for Improved Voice Conversion","date":"2021-11-03","arxiv_id":"2111.02392","repositories_listed":2,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/a-comparison-of-discrete-and-soft-speech#ran","syntology_url":"https://syntology.ai/paper/2111.02392","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.02392"}},"official":{"repos":["bshall/soft-vc"],"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/topological-relational-learning-on-graphs","slug":"topological-relational-learning-on-graphs","title":"Topological Relational Learning on Graphs","date":"2021-10-29","arxiv_id":"2110.15529","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":1,"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/topological-relational-learning-on-graphs#ran","syntology_url":"https://syntology.ai/paper/2110.15529","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.15529"}},"official":{"repos":["tri-gnn/tri-gnn"],"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/self-supervised-representation-learning-on-1","slug":"self-supervised-representation-learning-on-1","title":"Hyper-Representations: Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction","date":"2021-10-28","arxiv_id":"2110.15288","repositories_listed":1,"syntology":{"n":15,"n_ran":9,"n_constructed":6,"n_ran_checked":9,"n_instrument":0,"n_unverified":6,"n_honours":0,"n_violates":1,"n_no_contract":8,"n_pointer_only":15,"phrase":"9 ran (of which 6 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 1 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/self-supervised-representation-learning-on-1#ran","syntology_url":"https://syntology.ai/paper/2110.15288","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.15288"}},"official":{"repos":["hsg-aiml/neurips_2021-weight_space_learning"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":6,"n_ran_no_instrument_failure":9,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/tribert-full-body-human-centric-audio-visual","slug":"tribert-full-body-human-centric-audio-visual","title":"TriBERT: Full-body Human-centric Audio-visual Representation Learning for Visual Sound Separation","date":"2021-10-26","arxiv_id":"2110.13412","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/tribert-full-body-human-centric-audio-visual#ran","syntology_url":"https://syntology.ai/paper/2110.13412","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.13412"}},"official":{"repos":["ubc-vision/tribert"],"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/practical-galaxy-morphology-tools-from-deep","slug":"practical-galaxy-morphology-tools-from-deep","title":"Practical Galaxy Morphology Tools from Deep Supervised Representation Learning","date":"2021-10-25","arxiv_id":"2110.12735","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":2,"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; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/practical-galaxy-morphology-tools-from-deep#ran","syntology_url":"https://syntology.ai/paper/2110.12735","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.12735"}},"official":{"repos":["mwalmsley/zoobot"],"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/contrastively-disentangled-sequential","slug":"contrastively-disentangled-sequential","title":"Contrastively Disentangled Sequential Variational Autoencoder","date":"2021-10-22","arxiv_id":"2110.12091","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":5,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":6,"phrase":"6 ran (of which 5 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/contrastively-disentangled-sequential#ran","syntology_url":"https://syntology.ai/paper/2110.12091","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.12091"}},"official":{"repos":["JunwenBai/C-DSVAE"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":5,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/wav2clip-learning-robust-audio","slug":"wav2clip-learning-robust-audio","title":"Wav2CLIP: Learning Robust Audio Representations From CLIP","date":"2021-10-21","arxiv_id":"2110.11499","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/wav2clip-learning-robust-audio#ran","syntology_url":"https://syntology.ai/paper/2110.11499","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.11499"}},"official":{"repos":["descriptinc/lyrebird-wav2clip"],"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/anisotropic-separable-set-abstraction-for","slug":"anisotropic-separable-set-abstraction-for","title":"ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning","date":"2021-10-20","arxiv_id":"2110.10538","repositories_listed":1,"syntology":{"n":12,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":10,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"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) · 10 unverified","sample_list":"/paper/anisotropic-separable-set-abstraction-for#ran","syntology_url":"https://syntology.ai/paper/2110.10538","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.10538"}},"official":{"repos":["guochengqian/assanet"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":10,"ran_from_kinds":["official"]}}},{"url":"/paper/understanding-dimensional-collapse-in-1","slug":"understanding-dimensional-collapse-in-1","title":"Understanding Dimensional Collapse in Contrastive Self-supervised Learning","date":"2021-10-18","arxiv_id":"2110.09348","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":3,"n_pointer_only":5,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 1 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/understanding-dimensional-collapse-in-1#ran","syntology_url":"https://syntology.ai/paper/2110.09348","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.09348"}},"official":{"repos":["facebookresearch/directclr"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/virtual-augmentation-supported-contrastive","slug":"virtual-augmentation-supported-contrastive","title":"Virtual Augmentation Supported Contrastive Learning of Sentence Representations","date":"2021-10-16","arxiv_id":"2110.08552","repositories_listed":2,"syntology":{"n":8,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":3,"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) · 3 unverified","sample_list":"/paper/virtual-augmentation-supported-contrastive#ran","syntology_url":"https://syntology.ai/paper/2110.08552","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.08552"}},"official":{"repos":["amazon-research/sentence-representations"],"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/speecht5-unified-modal-encoder-decoder-pre","slug":"speecht5-unified-modal-encoder-decoder-pre","title":"SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing","date":"2021-10-14","arxiv_id":"2110.07205","repositories_listed":6,"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/speecht5-unified-modal-encoder-decoder-pre#ran","syntology_url":"https://syntology.ai/paper/2110.07205","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.07205"}},"official":{"repos":["microsoft/speecht5"],"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/self-supervised-learning-by-estimating-twin-1","slug":"self-supervised-learning-by-estimating-twin-1","title":"Self-Supervised Learning by Estimating Twin Class Distributions","date":"2021-10-14","arxiv_id":"2110.07402","repositories_listed":2,"syntology":{"n":15,"n_ran":9,"n_constructed":0,"n_ran_checked":5,"n_instrument":4,"n_unverified":6,"n_honours":1,"n_violates":0,"n_no_contract":4,"n_pointer_only":4,"phrase":"9 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; 4 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/self-supervised-learning-by-estimating-twin-1#ran","syntology_url":"https://syntology.ai/paper/2110.07402","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.07402"}},"official":{"repos":["bytedance/TWIST"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/the-deep-generative-decoder-using-map-1","slug":"the-deep-generative-decoder-using-map-1","title":"The Deep Generative Decoder: MAP estimation of representations improves modeling of single-cell RNA data","date":"2021-10-13","arxiv_id":"2110.06672","repositories_listed":2,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":0,"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) · 0 unverified","sample_list":"/paper/the-deep-generative-decoder-using-map-1#ran","syntology_url":"https://syntology.ai/paper/2110.06672","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.06672"}},"official":{"repos":["Center-for-Health-Data-Science/scDGD"],"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":["named_in_paper","official"]}}},{"url":"/paper/learning-temporally-consistent-1","slug":"learning-temporally-consistent-1","title":"Learning Temporally-Consistent Representations for Data-Efficient Reinforcement Learning","date":"2021-10-11","arxiv_id":"2110.04935","repositories_listed":2,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":2,"n_instrument":4,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":4,"phrase":"6 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; 4 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/learning-temporally-consistent-1#ran","syntology_url":"https://syntology.ai/paper/2110.04935","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.04935"}},"official":{"repos":["anon-researcher-repo/ksl"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/learning-temporally-causal-latent-processes","slug":"learning-temporally-causal-latent-processes","title":"Learning Temporally Causal Latent Processes from General Temporal Data","date":"2021-10-11","arxiv_id":"2110.05428","repositories_listed":2,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"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) · 1 unverified","sample_list":"/paper/learning-temporally-causal-latent-processes#ran","syntology_url":"https://syntology.ai/paper/2110.05428","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.05428"}},"official":{"repos":["weirayao/leap"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["community","listed"]}}},{"url":"/paper/multi-class-cell-detection-using-spatial-1","slug":"multi-class-cell-detection-using-spatial-1","title":"Multi-Class Cell Detection Using Spatial Context Representation","date":"2021-10-10","arxiv_id":"2110.04886","repositories_listed":2,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/multi-class-cell-detection-using-spatial-1#ran","syntology_url":"https://syntology.ai/paper/2110.04886","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.04886"}},"official":{"repos":["topoxlab/mcspatnet"],"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/clip-adapter-better-vision-language-models","slug":"clip-adapter-better-vision-language-models","title":"CLIP-Adapter: Better Vision-Language Models with Feature Adapters","date":"2021-10-09","arxiv_id":"2110.04544","repositories_listed":3,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"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) · 0 unverified","sample_list":"/paper/clip-adapter-better-vision-language-models#ran","syntology_url":"https://syntology.ai/paper/2110.04544","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.04544"}},"official":{"repos":["gaopengcuhk/clip-adapter"],"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/vector-quantized-image-modeling-with-improved-1","slug":"vector-quantized-image-modeling-with-improved-1","title":"Vector-quantized Image Modeling with Improved VQGAN","date":"2021-10-09","arxiv_id":"2110.04627","repositories_listed":5,"syntology":{"n":9,"n_ran":9,"n_constructed":0,"n_ran_checked":7,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":7,"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, 0 violated, 7 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/vector-quantized-image-modeling-with-improved-1#ran","syntology_url":"https://syntology.ai/paper/2110.04627","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.04627"}},"official":null}},{"url":"/paper/subtab-subsetting-features-of-tabular-data","slug":"subtab-subsetting-features-of-tabular-data","title":"SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning","date":"2021-10-08","arxiv_id":"2110.04361","repositories_listed":2,"syntology":{"n":14,"n_ran":8,"n_constructed":0,"n_ran_checked":5,"n_instrument":3,"n_unverified":6,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"8 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; 3 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/subtab-subsetting-features-of-tabular-data#ran","syntology_url":"https://syntology.ai/paper/2110.04361","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.04361"}},"official":null}},{"url":"/paper/learning-3d-representations-of-molecular-1","slug":"learning-3d-representations-of-molecular-1","title":"Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations","date":"2021-10-08","arxiv_id":"2110.04383","repositories_listed":1,"syntology":{"n":12,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/learning-3d-representations-of-molecular-1#ran","syntology_url":"https://syntology.ai/paper/2110.04383","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.04383"}},"official":{"repos":["keiradams/chiro"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/sharp-learning-bounds-for-contrastive","slug":"sharp-learning-bounds-for-contrastive","title":"On the Surrogate Gap between Contrastive and Supervised Losses","date":"2021-10-06","arxiv_id":"2110.02501","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"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) · 0 unverified","sample_list":"/paper/sharp-learning-bounds-for-contrastive#ran","syntology_url":"https://syntology.ai/paper/2110.02501","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.02501"}},"official":{"repos":["nzw0301/gap-contrastive-and-supervised-losses"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/debiased-graph-contrastive-learning","slug":"debiased-graph-contrastive-learning","title":"ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning","date":"2021-10-05","arxiv_id":"2110.02027","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":4,"phrase":"3 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; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/debiased-graph-contrastive-learning#ran","syntology_url":"https://syntology.ai/paper/2110.02027","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.02027"}},"official":{"repos":["junxia97/progcl"],"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-motion-representation-learning","slug":"unsupervised-motion-representation-learning","title":"Unsupervised Motion Representation Learning with Capsule Autoencoders","date":"2021-10-01","arxiv_id":"2110.00529","repositories_listed":1,"syntology":{"n":20,"n_ran":15,"n_constructed":4,"n_ran_checked":8,"n_instrument":7,"n_unverified":5,"n_honours":1,"n_violates":2,"n_no_contract":5,"n_pointer_only":0,"phrase":"15 ran (of which 4 constructed an object rather than computing a result; 8 with no instrument failure: 1 honoured, 2 violated, 5 with no contract checked; 7 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/unsupervised-motion-representation-learning#ran","syntology_url":"https://syntology.ai/paper/2110.00529","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.00529"}},"official":{"repos":["ZiweiXU/CapsuleMotion"],"state":"official (archive's flag): 15 ran","n_ran":15,"n_constructed":4,"n_ran_no_instrument_failure":8,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/learning-compact-representations-of-neural","slug":"learning-compact-representations-of-neural","title":"Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM)","date":"2021-10-01","arxiv_id":"2110.00684","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":1,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"2 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; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/learning-compact-representations-of-neural#ran","syntology_url":"https://syntology.ai/paper/2110.00684","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.00684"}},"official":{"repos":["jayroxis/dam-pytorch"],"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","unlocated"]}}},{"url":"/paper/scalable-rule-based-representation-learning","slug":"scalable-rule-based-representation-learning","title":"Scalable Rule-Based Representation Learning for Interpretable Classification","date":"2021-09-30","arxiv_id":"2109.15103","repositories_listed":2,"syntology":{"n":6,"n_ran":6,"n_constructed":6,"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 6 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; every one of the 6 samples that ran constructed an object rather than computing a result","sample_list":"/paper/scalable-rule-based-representation-learning#ran","syntology_url":"https://syntology.ai/paper/2109.15103","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.15103"}},"official":{"repos":["12wang3/rrl"],"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/chemical-reaction-aware-molecule","slug":"chemical-reaction-aware-molecule","title":"Chemical-Reaction-Aware Molecule Representation Learning","date":"2021-09-21","arxiv_id":"2109.09888","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":1,"n_honours":0,"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; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/chemical-reaction-aware-molecule#ran","syntology_url":"https://syntology.ai/paper/2109.09888","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.09888"}},"official":{"repos":["hwwang55/MolR"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/conquer-contextual-query-aware-ranking-for","slug":"conquer-contextual-query-aware-ranking-for","title":"CONQUER: Contextual Query-aware Ranking for Video Corpus Moment Retrieval","date":"2021-09-21","arxiv_id":"2109.10016","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/conquer-contextual-query-aware-ranking-for#ran","syntology_url":"https://syntology.ai/paper/2109.10016","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.10016"}},"official":{"repos":["houzhijian/conquer"],"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/autogcl-automated-graph-contrastive-learning","slug":"autogcl-automated-graph-contrastive-learning","title":"AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators","date":"2021-09-21","arxiv_id":"2109.10259","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":1,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":1,"n_no_contract":1,"n_pointer_only":3,"phrase":"3 ran (of which 1 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 1 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/autogcl-automated-graph-contrastive-learning#ran","syntology_url":"https://syntology.ai/paper/2109.10259","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.10259"}},"official":{"repos":["Somedaywilldo/AutoGCL"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":1,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/distilling-linguistic-context-for-language","slug":"distilling-linguistic-context-for-language","title":"Distilling Linguistic Context for Language Model Compression","date":"2021-09-17","arxiv_id":"2109.08359","repositories_listed":1,"syntology":{"n":11,"n_ran":8,"n_constructed":0,"n_ran_checked":7,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"8 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; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/distilling-linguistic-context-for-language#ran","syntology_url":"https://syntology.ai/paper/2109.08359","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.08359"}},"official":{"repos":["geondopark/ckd"],"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":["official"]}}},{"url":"/paper/online-unsupervised-learning-of-visual","slug":"online-unsupervised-learning-of-visual","title":"Online Unsupervised Learning of Visual Representations and Categories","date":"2021-09-13","arxiv_id":"2109.05675","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/online-unsupervised-learning-of-visual#ran","syntology_url":"https://syntology.ai/paper/2109.05675","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.05675"}},"official":{"repos":["renmengye/online-unsup-proto-net"],"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/cross-domain-robot-imitation-with-invariant","slug":"cross-domain-robot-imitation-with-invariant","title":"Cross Domain Robot Imitation with Invariant Representation","date":"2021-09-13","arxiv_id":"2109.05940","repositories_listed":1,"syntology":{"n":11,"n_ran":10,"n_constructed":0,"n_ran_checked":8,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":2,"phrase":"10 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; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/cross-domain-robot-imitation-with-invariant#ran","syntology_url":"https://syntology.ai/paper/2109.05940","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.05940"}},"official":{"repos":["zhaohengyin/irgail_example"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/pairwise-supervised-contrastive-learning-of","slug":"pairwise-supervised-contrastive-learning-of","title":"Pairwise Supervised Contrastive Learning of Sentence Representations","date":"2021-09-12","arxiv_id":"2109.05424","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/pairwise-supervised-contrastive-learning-of#ran","syntology_url":"https://syntology.ai/paper/2109.05424","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.05424"}},"official":{"repos":["amazon-research/sentence-representations"],"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/box-embeddings-an-open-source-library-for","slug":"box-embeddings-an-open-source-library-for","title":"Box Embeddings: An open-source library for representation learning using geometric structures","date":"2021-09-10","arxiv_id":"2109.04997","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":1,"n_ran_checked":1,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"3 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; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/box-embeddings-an-open-source-library-for#ran","syntology_url":"https://syntology.ai/paper/2109.04997","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.04997"}},"official":{"repos":["iesl/box-embeddings"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/desiderata-for-representation-learning-a","slug":"desiderata-for-representation-learning-a","title":"Desiderata for Representation Learning: A Causal Perspective","date":"2021-09-08","arxiv_id":"2109.03795","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":2,"n_instrument":2,"n_unverified":1,"n_honours":1,"n_violates":1,"n_no_contract":0,"n_pointer_only":0,"phrase":"4 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; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/desiderata-for-representation-learning-a#ran","syntology_url":"https://syntology.ai/paper/2109.03795","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.03795"}},"official":null}},{"url":"/paper/sornet-spatial-object-centric-representations","slug":"sornet-spatial-object-centric-representations","title":"SORNet: Spatial Object-Centric Representations for Sequential Manipulation","date":"2021-09-08","arxiv_id":"2109.03891","repositories_listed":1,"syntology":{"n":7,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/sornet-spatial-object-centric-representations#ran","syntology_url":"https://syntology.ai/paper/2109.03891","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.03891"}},"official":{"repos":["wentaoyuan/sornet"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/zero-shot-open-set-detection-by-extending","slug":"zero-shot-open-set-detection-by-extending","title":"Zero-Shot Out-of-Distribution Detection Based on the Pre-trained Model CLIP","date":"2021-09-06","arxiv_id":"2109.02748","repositories_listed":2,"syntology":{"n":11,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":10,"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) · 10 unverified","sample_list":"/paper/zero-shot-open-set-detection-by-extending#ran","syntology_url":"https://syntology.ai/paper/2109.02748","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.02748"}},"official":{"repos":["sesmae/zoc"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":10,"ran_from_kinds":["official"]}}},{"url":"/paper/dual-transfer-learning-for-event-based-end","slug":"dual-transfer-learning-for-event-based-end","title":"Dual Transfer Learning for Event-based End-task Prediction via Pluggable Event to Image Translation","date":"2021-09-04","arxiv_id":"2109.01801","repositories_listed":1,"syntology":{"n":10,"n_ran":7,"n_constructed":1,"n_ran_checked":5,"n_instrument":2,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"7 ran (of which 1 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/dual-transfer-learning-for-event-based-end#ran","syntology_url":"https://syntology.ai/paper/2109.01801","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.01801"}},"official":{"repos":["addisonwang2013/dtl"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":1,"n_ran_no_instrument_failure":5,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/learning-to-prompt-for-vision-language-models","slug":"learning-to-prompt-for-vision-language-models","title":"Learning to Prompt for Vision-Language Models","date":"2021-09-02","arxiv_id":"2109.01134","repositories_listed":18,"syntology":{"n":12,"n_ran":3,"n_constructed":1,"n_ran_checked":2,"n_instrument":1,"n_unverified":9,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"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) · 9 unverified","sample_list":"/paper/learning-to-prompt-for-vision-language-models#ran","syntology_url":"https://syntology.ai/paper/2109.01134","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.01134"}},"official":{"repos":["kaiyangzhou/coop"],"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/spatio-temporal-self-supervised","slug":"spatio-temporal-self-supervised","title":"Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds","date":"2021-09-01","arxiv_id":"2109.00179","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/spatio-temporal-self-supervised#ran","syntology_url":"https://syntology.ai/paper/2109.00179","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.00179"}},"official":{"repos":["yichen928/STRL"],"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/webqa-multihop-and-multimodal-qa","slug":"webqa-multihop-and-multimodal-qa","title":"WebQA: Multihop and Multimodal QA","date":"2021-09-01","arxiv_id":"2109.00590","repositories_listed":3,"syntology":{"n":13,"n_ran":10,"n_constructed":0,"n_ran_checked":8,"n_instrument":2,"n_unverified":3,"n_honours":2,"n_violates":0,"n_no_contract":6,"n_pointer_only":12,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 2 honoured, 0 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/webqa-multihop-and-multimodal-qa#ran","syntology_url":"https://syntology.ai/paper/2109.00590","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.00590"}},"official":null}},{"url":"/paper/a-partition-filter-network-for-joint-entity","slug":"a-partition-filter-network-for-joint-entity","title":"A Partition Filter Network for Joint Entity and Relation Extraction","date":"2021-08-27","arxiv_id":"2108.12202","repositories_listed":1,"syntology":{"n":7,"n_ran":5,"n_constructed":3,"n_ran_checked":4,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"5 ran (of which 3 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) · 2 unverified","sample_list":"/paper/a-partition-filter-network-for-joint-entity#ran","syntology_url":"https://syntology.ai/paper/2108.12202","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.12202"}},"official":{"repos":["Coopercoppers/PFN"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":3,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/geometry-aware-self-training-for-unsupervised","slug":"geometry-aware-self-training-for-unsupervised","title":"Geometry-Aware Self-Training for Unsupervised Domain Adaptationon Object Point Clouds","date":"2021-08-20","arxiv_id":"2108.09169","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/geometry-aware-self-training-for-unsupervised#ran","syntology_url":"https://syntology.ai/paper/2108.09169","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.09169"}},"official":{"repos":["zou-longkun/gast"],"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/mr-tydi-a-multi-lingual-benchmark-for-dense","slug":"mr-tydi-a-multi-lingual-benchmark-for-dense","title":"Mr. TyDi: A Multi-lingual Benchmark for Dense Retrieval","date":"2021-08-19","arxiv_id":"2108.08787","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/mr-tydi-a-multi-lingual-benchmark-for-dense#ran","syntology_url":"https://syntology.ai/paper/2108.08787","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.08787"}},"official":{"repos":["castorini/mr.tydi"],"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/learning-by-aligning-visible-infrared-person","slug":"learning-by-aligning-visible-infrared-person","title":"Learning by Aligning: Visible-Infrared Person Re-identification using Cross-Modal Correspondences","date":"2021-08-17","arxiv_id":"2108.07422","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/learning-by-aligning-visible-infrared-person#ran","syntology_url":"https://syntology.ai/paper/2108.07422","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.07422"}},"official":null}},{"url":"/paper/collaborative-unsupervised-visual","slug":"collaborative-unsupervised-visual","title":"Collaborative Unsupervised Visual Representation Learning from Decentralized Data","date":"2021-08-14","arxiv_id":"2108.06492","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":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) · 3 unverified","sample_list":"/paper/collaborative-unsupervised-visual#ran","syntology_url":"https://syntology.ai/paper/2108.06492","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.06492"}},"official":{"repos":["EasyFL-AI/EasyFL"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/graph-trend-networks-for-recommendations","slug":"graph-trend-networks-for-recommendations","title":"Graph Trend Filtering Networks for Recommendations","date":"2021-08-12","arxiv_id":"2108.05552","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/graph-trend-networks-for-recommendations#ran","syntology_url":"https://syntology.ai/paper/2108.05552","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.05552"}},"official":{"repos":["wenqifan03/gtn-sigir2022"],"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/learning-deep-multimodal-feature","slug":"learning-deep-multimodal-feature","title":"Learning Deep Multimodal Feature Representation with Asymmetric Multi-layer Fusion","date":"2021-08-11","arxiv_id":"2108.05009","repositories_listed":1,"syntology":{"n":11,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":5,"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) · 5 unverified","sample_list":"/paper/learning-deep-multimodal-feature#ran","syntology_url":"https://syntology.ai/paper/2108.05009","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.05009"}},"official":{"repos":["yikaiw/AsymFusion"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/representation-learning-for-remote-sensing-an","slug":"representation-learning-for-remote-sensing-an","title":"Representation Learning for Remote Sensing: An Unsupervised Sensor Fusion Approach","date":"2021-08-11","arxiv_id":"2108.05094","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":3,"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/representation-learning-for-remote-sensing-an#ran","syntology_url":"https://syntology.ai/paper/2108.05094","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.05094"}},"official":{"repos":["descarteslabs/contrastive_sensor_fusion"],"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/skeleton-contrastive-3d-action-representation","slug":"skeleton-contrastive-3d-action-representation","title":"Skeleton-Contrastive 3D Action Representation Learning","date":"2021-08-08","arxiv_id":"2108.03656","repositories_listed":1,"syntology":{"n":7,"n_ran":4,"n_constructed":0,"n_ran_checked":1,"n_instrument":3,"n_unverified":3,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":7,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/skeleton-contrastive-3d-action-representation#ran","syntology_url":"https://syntology.ai/paper/2108.03656","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.03656"}},"official":{"repos":["fmthoker/skeleton-contrast"],"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","unlocated"]}}},{"url":"/paper/dolg-single-stage-image-retrieval-with-deep","slug":"dolg-single-stage-image-retrieval-with-deep","title":"DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features","date":"2021-08-06","arxiv_id":"2108.02927","repositories_listed":5,"syntology":{"n":23,"n_ran":17,"n_constructed":0,"n_ran_checked":17,"n_instrument":0,"n_unverified":6,"n_honours":0,"n_violates":0,"n_no_contract":17,"n_pointer_only":0,"phrase":"17 ran (of which 0 constructed an object rather than computing a result; 17 with no instrument failure: 0 honoured, 0 violated, 17 with no contract checked; 0 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/dolg-single-stage-image-retrieval-with-deep#ran","syntology_url":"https://syntology.ai/paper/2108.02927","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.02927"}},"official":{"repos":["feymanpriv/DOLG"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/video-contrastive-learning-with-global","slug":"video-contrastive-learning-with-global","title":"Video Contrastive Learning with Global Context","date":"2021-08-05","arxiv_id":"2108.02722","repositories_listed":1,"syntology":{"n":8,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"3 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; 2 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/video-contrastive-learning-with-global#ran","syntology_url":"https://syntology.ai/paper/2108.02722","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.02722"}},"official":{"repos":["amazon-research/video-contrastive-learning"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/enhancing-self-supervised-video","slug":"enhancing-self-supervised-video","title":"Enhancing Self-supervised Video Representation Learning via Multi-level Feature Optimization","date":"2021-08-04","arxiv_id":"2108.02183","repositories_listed":1,"syntology":{"n":8,"n_ran":6,"n_constructed":4,"n_ran_checked":5,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":8,"phrase":"6 ran (of which 4 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) · 2 unverified","sample_list":"/paper/enhancing-self-supervised-video#ran","syntology_url":"https://syntology.ai/paper/2108.02183","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.02183"}},"official":{"repos":["shvdiwnkozbw/video-representation-via-multi-level-optimization"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":4,"n_ran_no_instrument_failure":5,"n_unverified":2,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/solo-learn-a-library-of-self-supervised","slug":"solo-learn-a-library-of-self-supervised","title":"Solo-learn: A Library of Self-supervised Methods for Visual Representation Learning","date":"2021-08-03","arxiv_id":"2108.01775","repositories_listed":4,"syntology":{"n":10,"n_ran":9,"n_constructed":0,"n_ran_checked":8,"n_instrument":1,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":7,"n_pointer_only":2,"phrase":"9 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; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/solo-learn-a-library-of-self-supervised#ran","syntology_url":"https://syntology.ai/paper/2108.01775","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.01775"}},"official":{"repos":["vturrisi/solo-learn","lightly-ai/lightly"],"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/representation-learning-for-neural-population","slug":"representation-learning-for-neural-population","title":"Representation learning for neural population activity with Neural Data Transformers","date":"2021-08-02","arxiv_id":"2108.01210","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":1,"n_no_contract":4,"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, 1 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/representation-learning-for-neural-population#ran","syntology_url":"https://syntology.ai/paper/2108.01210","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.01210"}},"official":{"repos":["snel-repo/neural-data-transformers"],"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/decaf-deep-extreme-classification-with-label","slug":"decaf-deep-extreme-classification-with-label","title":"DECAF: Deep Extreme Classification with Label Features","date":"2021-08-01","arxiv_id":"2108.00368","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":1,"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/decaf-deep-extreme-classification-with-label#ran","syntology_url":"https://syntology.ai/paper/2108.00368","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.00368"}},"official":{"repos":["Extreme-classification/DECAF"],"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/eclare-extreme-classification-with-label","slug":"eclare-extreme-classification-with-label","title":"ECLARE: Extreme Classification with Label Graph Correlations","date":"2021-07-31","arxiv_id":"2108.00261","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/eclare-extreme-classification-with-label#ran","syntology_url":"https://syntology.ai/paper/2108.00261","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.00261"}},"official":{"repos":["Extreme-classification/ECLARE"],"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/graph-constrained-data-representation","slug":"graph-constrained-data-representation","title":"Graph Constrained Data Representation Learning for Human Motion Segmentation","date":"2021-07-28","arxiv_id":"2107.13362","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":1,"n_instrument":3,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":4,"phrase":"4 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; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/graph-constrained-data-representation#ran","syntology_url":"https://syntology.ai/paper/2107.13362","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.13362"}},"official":{"repos":["mdimiccoli/gcrl-for-hms"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/mwp-bert-a-strong-baseline-for-math-word","slug":"mwp-bert-a-strong-baseline-for-math-word","title":"MWP-BERT: Numeracy-Augmented Pre-training for Math Word Problem Solving","date":"2021-07-28","arxiv_id":"2107.13435","repositories_listed":1,"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":4,"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/mwp-bert-a-strong-baseline-for-math-word#ran","syntology_url":"https://syntology.ai/paper/2107.13435","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.13435"}},"official":{"repos":["lzhenwen/mwp-bert"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/conditional-sound-generation-using-neural","slug":"conditional-sound-generation-using-neural","title":"Conditional Sound Generation Using Neural Discrete Time-Frequency Representation Learning","date":"2021-07-21","arxiv_id":"2107.09998","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/conditional-sound-generation-using-neural#ran","syntology_url":"https://syntology.ai/paper/2107.09998","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.09998"}},"official":{"repos":["liuxubo717/sound_generation"],"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/visual-representation-learning-does-not","slug":"visual-representation-learning-does-not","title":"Visual Representation Learning Does Not Generalize Strongly Within the Same Domain","date":"2021-07-17","arxiv_id":"2107.08221","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":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) · 1 unverified","sample_list":"/paper/visual-representation-learning-does-not#ran","syntology_url":"https://syntology.ai/paper/2107.08221","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.08221"}},"official":{"repos":["bethgelab/InDomainGeneralizationBenchmark"],"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/align-before-fuse-vision-and-language","slug":"align-before-fuse-vision-and-language","title":"Align before Fuse: Vision and Language Representation Learning with Momentum Distillation","date":"2021-07-16","arxiv_id":"2107.07651","repositories_listed":6,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":1,"n_instrument":3,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":3,"phrase":"4 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; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/align-before-fuse-vision-and-language#ran","syntology_url":"https://syntology.ai/paper/2107.07651","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.07651"}},"official":{"repos":["salesforce/lavis"],"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/self-supervised-learning-framework-for-remote","slug":"self-supervised-learning-framework-for-remote","title":"Self-supervised Representation Learning Framework for Remote Physiological Measurement Using Spatiotemporal Augmentation Loss","date":"2021-07-16","arxiv_id":"2107.07695","repositories_listed":1,"syntology":{"n":6,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"3 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; 2 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/self-supervised-learning-framework-for-remote#ran","syntology_url":"https://syntology.ai/paper/2107.07695","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.07695"}},"official":{"repos":["Dylan-H-Wang/SLF-RPM"],"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/multibench-multiscale-benchmarks-for","slug":"multibench-multiscale-benchmarks-for","title":"MultiBench: Multiscale Benchmarks for Multimodal Representation Learning","date":"2021-07-15","arxiv_id":"2107.07502","repositories_listed":3,"syntology":{"n":16,"n_ran":11,"n_constructed":0,"n_ran_checked":11,"n_instrument":0,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":1,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 0 violated, 11 with no contract checked; 0 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/multibench-multiscale-benchmarks-for#ran","syntology_url":"https://syntology.ai/paper/2107.07502","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.07502"}},"official":{"repos":["pliang279/MultiBench","pliang279/awesome-multimodal-ml"],"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":["found_in_text","official"]}}},{"url":"/paper/nucmm-dataset-3d-neuronal-nuclei-instance","slug":"nucmm-dataset-3d-neuronal-nuclei-instance","title":"NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter Scale","date":"2021-07-13","arxiv_id":"2107.05840","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/nucmm-dataset-3d-neuronal-nuclei-instance#ran","syntology_url":"https://syntology.ai/paper/2107.05840","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.05840"}},"official":{"repos":["zudi-lin/pytorch_connectomics"],"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/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/contrastive-multimodal-fusion-with","slug":"contrastive-multimodal-fusion-with","title":"Contrastive Multimodal Fusion with TupleInfoNCE","date":"2021-07-06","arxiv_id":"2107.02575","repositories_listed":1,"syntology":{"n":7,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":4,"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) · 4 unverified","sample_list":"/paper/contrastive-multimodal-fusion-with#ran","syntology_url":"https://syntology.ai/paper/2107.02575","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.02575"}},"official":{"repos":["hoi4d/TupleInfoNCE"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/continual-contrastive-self-supervised","slug":"continual-contrastive-self-supervised","title":"Continual Contrastive Learning for Image Classification","date":"2021-07-05","arxiv_id":"2107.01776","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":2,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/continual-contrastive-self-supervised#ran","syntology_url":"https://syntology.ai/paper/2107.01776","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.01776"}},"official":{"repos":["VDIGPKU/ContinualContrastiveLearning"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/systematic-evaluation-of-causal-discovery-in-1","slug":"systematic-evaluation-of-causal-discovery-in-1","title":"Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning","date":"2021-07-02","arxiv_id":"2107.00848","repositories_listed":1,"syntology":{"n":14,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":0,"phrase":"9 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; 0 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/systematic-evaluation-of-causal-discovery-in-1#ran","syntology_url":"https://syntology.ai/paper/2107.00848","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.00848"}},"official":{"repos":["dido1998/CausalMBRL"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/pretext-tasks-selection-for-multitask-self","slug":"pretext-tasks-selection-for-multitask-self","title":"Pretext Tasks selection for multitask self-supervised speech representation learning","date":"2021-07-01","arxiv_id":"2107.00594","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/pretext-tasks-selection-for-multitask-self#ran","syntology_url":"https://syntology.ai/paper/2107.00594","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.00594"}},"official":{"repos":["salah-zaiem/PL-groupselection"],"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/generalization-and-robustness-implications-in","slug":"generalization-and-robustness-implications-in","title":"Generalization and Robustness Implications in Object-Centric Learning","date":"2021-07-01","arxiv_id":"2107.00637","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/generalization-and-robustness-implications-in#ran","syntology_url":"https://syntology.ai/paper/2107.00637","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.00637"}},"official":{"repos":["addtt/object-centric-library"],"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/interventional-assays-for-the-latent-space-of","slug":"interventional-assays-for-the-latent-space-of","title":"Exploring the Latent Space of Autoencoders with Interventional Assays","date":"2021-06-30","arxiv_id":"2106.16091","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/interventional-assays-for-the-latent-space-of#ran","syntology_url":"https://syntology.ai/paper/2106.16091","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.16091"}},"official":{"repos":["felixludos/latent-responses"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/scarf-self-supervised-contrastive-learning","slug":"scarf-self-supervised-contrastive-learning","title":"SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption","date":"2021-06-29","arxiv_id":"2106.15147","repositories_listed":1,"syntology":{"n":3,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":2,"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) · 2 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/scarf-self-supervised-contrastive-learning#ran","syntology_url":"https://syntology.ai/paper/2106.15147","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.15147"}},"official":null}},{"url":"/paper/a-representation-learning-perspective-on-the","slug":"a-representation-learning-perspective-on-the","title":"A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-Learning","date":"2021-06-29","arxiv_id":"2106.15615","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":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/a-representation-learning-perspective-on-the#ran","syntology_url":"https://syntology.ai/paper/2106.15615","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.15615"}},"official":{"repos":["nsaunshi/meta_tr_val_split"],"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/opencos-contrastive-semi-supervised-learning-1","slug":"opencos-contrastive-semi-supervised-learning-1","title":"OpenCoS: Contrastive Semi-supervised Learning for Handling Open-set Unlabeled Data","date":"2021-06-29","arxiv_id":"2107.08943","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/opencos-contrastive-semi-supervised-learning-1#ran","syntology_url":"https://syntology.ai/paper/2107.08943","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.08943"}},"official":{"repos":["alinlab/opencos"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/hyperbolic-busemann-learning-with-ideal","slug":"hyperbolic-busemann-learning-with-ideal","title":"Hyperbolic Busemann Learning with Ideal Prototypes","date":"2021-06-28","arxiv_id":"2106.14472","repositories_listed":1,"syntology":{"n":4,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":4,"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) · 2 unverified","sample_list":"/paper/hyperbolic-busemann-learning-with-ideal#ran","syntology_url":"https://syntology.ai/paper/2106.14472","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.14472"}},"official":{"repos":["minaghadimiatigh/hyperbolic-busemann-learning"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/time-series-representation-learning-via","slug":"time-series-representation-learning-via","title":"Time-Series Representation Learning via Temporal and Contextual Contrasting","date":"2021-06-26","arxiv_id":"2106.14112","repositories_listed":2,"syntology":{"n":2,"n_ran":2,"n_constructed":1,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"2 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; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/time-series-representation-learning-via#ran","syntology_url":"https://syntology.ai/paper/2106.14112","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.14112"}},"official":{"repos":["emadeldeen24/TS-TCC"],"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":["listed","official"]}}},{"url":"/paper/nodepiece-compositional-and-parameter","slug":"nodepiece-compositional-and-parameter","title":"NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs","date":"2021-06-23","arxiv_id":"2106.12144","repositories_listed":4,"syntology":{"n":7,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":3,"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) · 3 unverified","sample_list":"/paper/nodepiece-compositional-and-parameter#ran","syntology_url":"https://syntology.ai/paper/2106.12144","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.12144"}},"official":{"repos":["migalkin/NodePiece"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["listed"]}}},{"url":"/paper/from-canonical-correlation-analysis-to-self","slug":"from-canonical-correlation-analysis-to-self","title":"From Canonical Correlation Analysis to Self-supervised Graph Neural Networks","date":"2021-06-23","arxiv_id":"2106.12484","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/from-canonical-correlation-analysis-to-self#ran","syntology_url":"https://syntology.ai/paper/2106.12484","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.12484"}},"official":{"repos":["hengruizhang98/CCA-SSG"],"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/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/unsupervised-object-level-representation","slug":"unsupervised-object-level-representation","title":"Unsupervised Object-Level Representation Learning from Scene Images","date":"2021-06-22","arxiv_id":"2106.11952","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"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) · 0 unverified","sample_list":"/paper/unsupervised-object-level-representation#ran","syntology_url":"https://syntology.ai/paper/2106.11952","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.11952"}},"official":{"repos":["jiahao000/orl"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}}],"record_sha256":"fe7293fcba47449169d9fea85042e0970d8bde08d8e6bd7b32136c7a74d9760f","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}