{"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/diversity/papers/ran/7","list_of":"/task/diversity","task":"Diversity","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":7,"pages_in_order":9,"rows_per_page":100,"rows":[601,700],"of":890,"counts":{"archive_papers_tagged":9051,"with_a_code_link":3166,"where_syntology_ran_a_sample":890,"not_listed_spam_title":0,"listed":9051,"listed_where_code_ran":890,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":736,"every_run_a_failure_of_syntologys_instrument":154,"listed_with_a_run_with_no_instrument_failure":736,"listed_every_run_a_failure_of_syntologys_instrument":154,"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/diversity/papers/ran/1","prev":"/task/diversity/papers/ran/6","next":"/task/diversity/papers/ran/8","papers":[{"url":"/paper/open-world-instance-segmentation-exploiting","slug":"open-world-instance-segmentation-exploiting","title":"Open-World Instance Segmentation: Exploiting Pseudo Ground Truth From Learned Pairwise Affinity","date":"2022-04-12","arxiv_id":"2204.06107","repositories_listed":1,"syntology":{"n":20,"n_ran":11,"n_constructed":0,"n_ran_checked":2,"n_instrument":9,"n_unverified":9,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":20,"phrase":"11 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; 9 where Syntology's instrument failed) · 9 unverified","sample_list":"/paper/open-world-instance-segmentation-exploiting#ran","syntology_url":"https://syntology.ai/paper/2204.06107","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2204.06107"}},"official":{"repos":["facebookresearch/Generic-Grouping"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":9,"ran_from_kinds":["official"]}}},{"url":"/paper/diverse-text-generation-via-variational","slug":"diverse-text-generation-via-variational","title":"Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process Priors","date":"2022-04-04","arxiv_id":"2204.01227","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/diverse-text-generation-via-variational#ran","syntology_url":"https://syntology.ai/paper/2204.01227","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2204.01227"}},"official":{"repos":["wyu-du/gp-vae"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/envedit-environment-editing-for-vision-and","slug":"envedit-environment-editing-for-vision-and","title":"EnvEdit: Environment Editing for Vision-and-Language Navigation","date":"2022-03-29","arxiv_id":"2203.15685","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/envedit-environment-editing-for-vision-and#ran","syntology_url":"https://syntology.ai/paper/2203.15685","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.15685"}},"official":{"repos":["jialuli-luka/envedit"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/physics-guided-generative-adversarial-1","slug":"physics-guided-generative-adversarial-1","title":"Physics Guided Deep Learning for Generative Design of Crystal Materials with Symmetry Constraints","date":"2022-03-27","arxiv_id":"2203.14352","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/physics-guided-generative-adversarial-1#ran","syntology_url":"https://syntology.ai/paper/2203.14352","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.14352"}},"official":{"repos":["MilesZhao/PGCGM"],"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/implicit-neural-representations-for-variable","slug":"implicit-neural-representations-for-variable","title":"Implicit Neural Representations for Variable Length Human Motion Generation","date":"2022-03-25","arxiv_id":"2203.13694","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/implicit-neural-representations-for-variable#ran","syntology_url":"https://syntology.ai/paper/2203.13694","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.13694"}},"official":{"repos":["pacerv/implicitmotion"],"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"]}}},{"url":"/paper/analyzing-generalization-of-vision-and","slug":"analyzing-generalization-of-vision-and","title":"Analyzing Generalization of Vision and Language Navigation to Unseen Outdoor Areas","date":"2022-03-25","arxiv_id":"2203.13838","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/analyzing-generalization-of-vision-and#ran","syntology_url":"https://syntology.ai/paper/2203.13838","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.13838"}},"official":{"repos":["raphael-sch/map2seq_vln"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/self-supervised-learning-of-adversarial","slug":"self-supervised-learning-of-adversarial","title":"Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake Detection","date":"2022-03-23","arxiv_id":"2203.12208","repositories_listed":1,"syntology":{"n":36,"n_ran":27,"n_constructed":2,"n_ran_checked":16,"n_instrument":11,"n_unverified":9,"n_honours":0,"n_violates":2,"n_no_contract":14,"n_pointer_only":0,"phrase":"27 ran (of which 2 constructed an object rather than computing a result; 16 with no instrument failure: 0 honoured, 2 violated, 14 with no contract checked; 11 where Syntology's instrument failed) · 9 unverified","sample_list":"/paper/self-supervised-learning-of-adversarial#ran","syntology_url":"https://syntology.ai/paper/2203.12208","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.12208"}},"official":{"repos":["liangchen527/sladd"],"state":"official (archive's flag): 27 ran","n_ran":27,"n_constructed":2,"n_ran_no_instrument_failure":16,"n_unverified":9,"ran_from_kinds":["official"]}}},{"url":"/paper/training-free-transformer-architecture-search","slug":"training-free-transformer-architecture-search","title":"Training-free Transformer Architecture Search","date":"2022-03-23","arxiv_id":"2203.12217","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":1,"n_honours":1,"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; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/training-free-transformer-architecture-search#ran","syntology_url":"https://syntology.ai/paper/2203.12217","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.12217"}},"official":null}},{"url":"/paper/a-unified-substrate-for-body-brain-co","slug":"a-unified-substrate-for-body-brain-co","title":"A Unified Substrate for Body-Brain Co-evolution","date":"2022-03-22","arxiv_id":"2203.12066","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":1,"n_ran_checked":2,"n_instrument":2,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"4 ran (of which 1 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/a-unified-substrate-for-body-brain-co#ran","syntology_url":"https://syntology.ai/paper/2203.12066","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.12066"}},"official":{"repos":["sidneyp/neural-cellular-robot-substrate"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":1,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/quality-controlled-paraphrase-generation","slug":"quality-controlled-paraphrase-generation","title":"Quality Controlled Paraphrase Generation","date":"2022-03-21","arxiv_id":"2203.10940","repositories_listed":1,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":4,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/quality-controlled-paraphrase-generation#ran","syntology_url":"https://syntology.ai/paper/2203.10940","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.10940"}},"official":{"repos":["ibm/quality-controlled-paraphrase-generation"],"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/raregan-generating-samples-for-rare-classes","slug":"raregan-generating-samples-for-rare-classes","title":"RareGAN: Generating Samples for Rare Classes","date":"2022-03-20","arxiv_id":"2203.10674","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/raregan-generating-samples-for-rare-classes#ran","syntology_url":"https://syntology.ai/paper/2203.10674","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.10674"}},"official":{"repos":["fjxmlzn/raregan"],"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/motionaug-augmentation-with-physical","slug":"motionaug-augmentation-with-physical","title":"MotionAug: Augmentation with Physical Correction for Human Motion Prediction","date":"2022-03-17","arxiv_id":"2203.09116","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":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) · 0 unverified","sample_list":"/paper/motionaug-augmentation-with-physical#ran","syntology_url":"https://syntology.ai/paper/2203.09116","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.09116"}},"official":{"repos":["meaten/motionaug"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/attribute-group-editing-for-reliable-few-shot","slug":"attribute-group-editing-for-reliable-few-shot","title":"Attribute Group Editing for Reliable Few-shot Image Generation","date":"2022-03-16","arxiv_id":"2203.08422","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":2,"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/attribute-group-editing-for-reliable-few-shot#ran","syntology_url":"https://syntology.ai/paper/2203.08422","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.08422"}},"official":{"repos":["unibester/age"],"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/on-redundancy-and-diversity-in-cell-based-1","slug":"on-redundancy-and-diversity-in-cell-based-1","title":"On Redundancy and Diversity in Cell-based Neural Architecture Search","date":"2022-03-16","arxiv_id":"2203.08887","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-redundancy-and-diversity-in-cell-based-1#ran","syntology_url":"https://syntology.ai/paper/2203.08887","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.08887"}},"official":{"repos":["xingchenwan/cell-based-nas-analysis"],"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/complex-evolutional-pattern-learning-for","slug":"complex-evolutional-pattern-learning-for","title":"Complex Evolutional Pattern Learning for Temporal Knowledge Graph Reasoning","date":"2022-03-15","arxiv_id":"2203.07782","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":1,"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/complex-evolutional-pattern-learning-for#ran","syntology_url":"https://syntology.ai/paper/2203.07782","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.07782"}},"official":{"repos":["lee-zix/cen"],"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/insetgan-for-full-body-image-generation","slug":"insetgan-for-full-body-image-generation","title":"InsetGAN for Full-Body Image Generation","date":"2022-03-14","arxiv_id":"2203.07293","repositories_listed":2,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/insetgan-for-full-body-image-generation#ran","syntology_url":"https://syntology.ai/paper/2203.07293","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.07293"}},"official":{"repos":["afruehstueck/insetGAN"],"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/the-principle-of-diversity-training-stronger","slug":"the-principle-of-diversity-training-stronger","title":"The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy","date":"2022-03-12","arxiv_id":"2203.06345","repositories_listed":1,"syntology":{"n":13,"n_ran":11,"n_constructed":0,"n_ran_checked":10,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":2,"phrase":"11 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; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/the-principle-of-diversity-training-stronger#ran","syntology_url":"https://syntology.ai/paper/2203.06345","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.06345"}},"official":{"repos":["vita-group/diverse-vit"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/back-to-reality-weakly-supervised-3d-object","slug":"back-to-reality-weakly-supervised-3d-object","title":"Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label Enhancement","date":"2022-03-10","arxiv_id":"2203.05238","repositories_listed":2,"syntology":{"n":25,"n_ran":20,"n_constructed":0,"n_ran_checked":16,"n_instrument":4,"n_unverified":5,"n_honours":2,"n_violates":0,"n_no_contract":14,"n_pointer_only":0,"phrase":"20 ran (of which 0 constructed an object rather than computing a result; 16 with no instrument failure: 2 honoured, 0 violated, 14 with no contract checked; 4 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/back-to-reality-weakly-supervised-3d-object#ran","syntology_url":"https://syntology.ai/paper/2203.05238","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.05238"}},"official":{"repos":["wyf-accept/backtoreality","xuxw98/backtoreality"],"state":"official (archive's flag): 20 ran","n_ran":20,"n_constructed":0,"n_ran_no_instrument_failure":16,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/l2cs-net-fine-grained-gaze-estimation-in","slug":"l2cs-net-fine-grained-gaze-estimation-in","title":"L2CS-Net: Fine-Grained Gaze Estimation in Unconstrained Environments","date":"2022-03-07","arxiv_id":"2203.03339","repositories_listed":2,"syntology":{"n":10,"n_ran":8,"n_constructed":0,"n_ran_checked":5,"n_instrument":3,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":4,"n_pointer_only":3,"phrase":"8 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; 3 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/l2cs-net-fine-grained-gaze-estimation-in#ran","syntology_url":"https://syntology.ai/paper/2203.03339","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.03339"}},"official":null}},{"url":"/paper/hierarchical-sketch-induction-for-paraphrase","slug":"hierarchical-sketch-induction-for-paraphrase","title":"Hierarchical Sketch Induction for Paraphrase Generation","date":"2022-03-07","arxiv_id":"2203.03463","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":1,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":1,"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; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/hierarchical-sketch-induction-for-paraphrase#ran","syntology_url":"https://syntology.ai/paper/2203.03463","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.03463"}},"official":{"repos":["tomhosking/hrq-vae"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":1,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/freeform-body-motion-generation-from-speech","slug":"freeform-body-motion-generation-from-speech","title":"Freeform Body Motion Generation from Speech","date":"2022-03-04","arxiv_id":"2203.02291","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/freeform-body-motion-generation-from-speech#ran","syntology_url":"https://syntology.ai/paper/2203.02291","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.02291"}},"official":{"repos":["thetempaccount/co-speech-motion-generation"],"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/biological-sequence-design-with-gflownets","slug":"biological-sequence-design-with-gflownets","title":"Biological Sequence Design with GFlowNets","date":"2022-03-02","arxiv_id":"2203.04115","repositories_listed":1,"syntology":{"n":7,"n_ran":4,"n_constructed":3,"n_ran_checked":3,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"4 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/biological-sequence-design-with-gflownets#ran","syntology_url":"https://syntology.ai/paper/2203.04115","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.04115"}},"official":{"repos":["mj10/bioseq-gfn-al"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/prune-and-tune-ensembles-low-cost-ensemble","slug":"prune-and-tune-ensembles-low-cost-ensemble","title":"Prune and Tune Ensembles: Low-Cost Ensemble Learning With Sparse Independent Subnetworks","date":"2022-02-23","arxiv_id":"2202.11782","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/prune-and-tune-ensembles-low-cost-ensemble#ran","syntology_url":"https://syntology.ai/paper/2202.11782","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.11782"}},"official":null}},{"url":"/paper/submodlib-a-submodular-optimization-library","slug":"submodlib-a-submodular-optimization-library","title":"Submodlib: A Submodular Optimization Library","date":"2022-02-22","arxiv_id":"2202.10680","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/submodlib-a-submodular-optimization-library#ran","syntology_url":"https://syntology.ai/paper/2202.10680","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.10680"}},"official":{"repos":["decile-team/submodlib"],"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"]}}},{"url":"/paper/deep-ensembles-work-but-are-they-necessary","slug":"deep-ensembles-work-but-are-they-necessary","title":"Deep Ensembles Work, But Are They Necessary?","date":"2022-02-14","arxiv_id":"2202.06985","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":3,"n_no_contract":0,"n_pointer_only":6,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 3 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/deep-ensembles-work-but-are-they-necessary#ran","syntology_url":"https://syntology.ai/paper/2202.06985","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.06985"}},"official":{"repos":["cellistigs/interp_ensembles"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/a-contrastive-framework-for-neural-text","slug":"a-contrastive-framework-for-neural-text","title":"A Contrastive Framework for Neural Text Generation","date":"2022-02-13","arxiv_id":"2202.06417","repositories_listed":2,"syntology":{"n":4,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/a-contrastive-framework-for-neural-text#ran","syntology_url":"https://syntology.ai/paper/2202.06417","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.06417"}},"official":{"repos":["yxuansu/simctg"],"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/inpars-data-augmentation-for-information","slug":"inpars-data-augmentation-for-information","title":"InPars: Data Augmentation for Information Retrieval using Large Language Models","date":"2022-02-10","arxiv_id":"2202.05144","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/inpars-data-augmentation-for-information#ran","syntology_url":"https://syntology.ai/paper/2202.05144","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.05144"}},"official":{"repos":["zetaalphavector/inpars"],"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/approximating-gradients-for-differentiable","slug":"approximating-gradients-for-differentiable","title":"Approximating Gradients for Differentiable Quality Diversity in Reinforcement Learning","date":"2022-02-08","arxiv_id":"2202.03666","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/approximating-gradients-for-differentiable#ran","syntology_url":"https://syntology.ai/paper/2202.03666","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.03666"}},"official":{"repos":["icaros-usc/dqd-rl"],"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/exploring-inter-channel-correlation-for-1","slug":"exploring-inter-channel-correlation-for-1","title":"Exploring Inter-Channel Correlation for Diversity-preserved KnowledgeDistillation","date":"2022-02-08","arxiv_id":"2202.03680","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":2,"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/exploring-inter-channel-correlation-for-1#ran","syntology_url":"https://syntology.ai/paper/2202.03680","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.03680"}},"official":{"repos":["adlab-autodrive/ickd"],"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/red-teaming-language-models-with-language","slug":"red-teaming-language-models-with-language","title":"Red Teaming Language Models with Language Models","date":"2022-02-07","arxiv_id":"2202.03286","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/red-teaming-language-models-with-language#ran","syntology_url":"https://syntology.ai/paper/2202.03286","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.03286"}},"official":null}},{"url":"/paper/lipschitz-constrained-unsupervised-skill-1","slug":"lipschitz-constrained-unsupervised-skill-1","title":"Lipschitz-constrained Unsupervised Skill Discovery","date":"2022-02-02","arxiv_id":"2202.00914","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/lipschitz-constrained-unsupervised-skill-1#ran","syntology_url":"https://syntology.ai/paper/2202.00914","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.00914"}},"official":null}},{"url":"/paper/improving-screening-processes-via-calibrated","slug":"improving-screening-processes-via-calibrated","title":"Improving Screening Processes via Calibrated Subset Selection","date":"2022-02-02","arxiv_id":"2202.01147","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/improving-screening-processes-via-calibrated#ran","syntology_url":"https://syntology.ai/paper/2202.01147","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.01147"}},"official":{"repos":["LequnWang/Improve-Screening-via-Calibrated-Subset-Selection"],"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/cic-contrastive-intrinsic-control-for-1","slug":"cic-contrastive-intrinsic-control-for-1","title":"CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery","date":"2022-02-01","arxiv_id":"2202.00161","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/cic-contrastive-intrinsic-control-for-1#ran","syntology_url":"https://syntology.ai/paper/2202.00161","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.00161"}},"official":null}},{"url":"/paper/neuraltailor-reconstructing-sewing-pattern","slug":"neuraltailor-reconstructing-sewing-pattern","title":"NeuralTailor: Reconstructing Sewing Pattern Structures from 3D Point Clouds of Garments","date":"2022-01-31","arxiv_id":"2201.13063","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/neuraltailor-reconstructing-sewing-pattern#ran","syntology_url":"https://syntology.ai/paper/2201.13063","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.13063"}},"official":{"repos":["maria-korosteleva/Garment-Pattern-Estimation"],"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"]}}},{"url":"/paper/trajectory-balance-improved-credit-assignment","slug":"trajectory-balance-improved-credit-assignment","title":"Trajectory balance: Improved credit assignment in GFlowNets","date":"2022-01-31","arxiv_id":"2201.13259","repositories_listed":4,"syntology":{"n":6,"n_ran":3,"n_constructed":1,"n_ran_checked":1,"n_instrument":2,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"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) · 3 unverified","sample_list":"/paper/trajectory-balance-improved-credit-assignment#ran","syntology_url":"https://syntology.ai/paper/2201.13259","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.13259"}},"official":{"repos":["gfnorg/gflownet"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/don-t-change-the-algorithm-change-the-data","slug":"don-t-change-the-algorithm-change-the-data","title":"Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning","date":"2022-01-31","arxiv_id":"2201.13425","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/don-t-change-the-algorithm-change-the-data#ran","syntology_url":"https://syntology.ai/paper/2201.13425","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.13425"}},"official":{"repos":["denisyarats/exorl"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/does-transliteration-help-multilingual","slug":"does-transliteration-help-multilingual","title":"Does Transliteration Help Multilingual Language Modeling?","date":"2022-01-29","arxiv_id":"2201.12501","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/does-transliteration-help-multilingual#ran","syntology_url":"https://syntology.ai/paper/2201.12501","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.12501"}},"official":{"repos":["ibraheem-moosa/xlm-indic"],"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/you-only-cut-once-boosting-data-augmentation","slug":"you-only-cut-once-boosting-data-augmentation","title":"You Only Cut Once: Boosting Data Augmentation with a Single Cut","date":"2022-01-28","arxiv_id":"2201.12078","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/you-only-cut-once-boosting-data-augmentation#ran","syntology_url":"https://syntology.ai/paper/2201.12078","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.12078"}},"official":{"repos":["junlinhan/yoco"],"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/the-effect-of-diversity-in-meta-learning-1","slug":"the-effect-of-diversity-in-meta-learning-1","title":"The Effect of Diversity in Meta-Learning","date":"2022-01-27","arxiv_id":"2201.11775","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/the-effect-of-diversity-in-meta-learning-1#ran","syntology_url":"https://syntology.ai/paper/2201.11775","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.11775"}},"official":{"repos":["RamnathKumar181/Task-Diversity-meta-learning"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/anomaly-detection-via-reverse-distillation","slug":"anomaly-detection-via-reverse-distillation","title":"Anomaly Detection via Reverse Distillation from One-Class Embedding","date":"2022-01-26","arxiv_id":"2201.10703","repositories_listed":5,"syntology":{"n":18,"n_ran":14,"n_constructed":8,"n_ran_checked":10,"n_instrument":4,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":15,"phrase":"14 ran (of which 8 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 4 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/anomaly-detection-via-reverse-distillation#ran","syntology_url":"https://syntology.ai/paper/2201.10703","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.10703"}},"official":{"repos":["hq-deng/RD4AD"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["listed","official","unlocated"]}}},{"url":"/paper/variational-model-inversion-attacks-1","slug":"variational-model-inversion-attacks-1","title":"Variational Model Inversion Attacks","date":"2022-01-26","arxiv_id":"2201.10787","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/variational-model-inversion-attacks-1#ran","syntology_url":"https://syntology.ai/paper/2201.10787","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.10787"}},"official":{"repos":["wangkua1/vmi"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/adaptpose-cross-dataset-adaptation-for-3d","slug":"adaptpose-cross-dataset-adaptation-for-3d","title":"AdaptPose: Cross-Dataset Adaptation for 3D Human Pose Estimation by Learnable Motion Generation","date":"2021-12-22","arxiv_id":"2112.11593","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":1,"n_no_contract":2,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 1 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/adaptpose-cross-dataset-adaptation-for-3d#ran","syntology_url":"https://syntology.ai/paper/2112.11593","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.11593"}},"official":{"repos":["mgholamikn/AdaptPose"],"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"]}}},{"url":"/paper/glide-towards-photorealistic-image-generation","slug":"glide-towards-photorealistic-image-generation","title":"GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models","date":"2021-12-20","arxiv_id":"2112.10741","repositories_listed":2,"syntology":{"n":15,"n_ran":9,"n_constructed":7,"n_ran_checked":8,"n_instrument":1,"n_unverified":6,"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) · 6 unverified","sample_list":"/paper/glide-towards-photorealistic-image-generation#ran","syntology_url":"https://syntology.ai/paper/2112.10741","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.10741"}},"official":{"repos":["openai/glide-text2im"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":7,"n_ran_no_instrument_failure":8,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/tackling-the-generative-learning-trilemma-1","slug":"tackling-the-generative-learning-trilemma-1","title":"Tackling the Generative Learning Trilemma with Denoising Diffusion GANs","date":"2021-12-15","arxiv_id":"2112.07804","repositories_listed":5,"syntology":{"n":12,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":6,"n_honours":0,"n_violates":1,"n_no_contract":5,"n_pointer_only":1,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 1 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/tackling-the-generative-learning-trilemma-1#ran","syntology_url":"https://syntology.ai/paper/2112.07804","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.07804"}},"official":{"repos":["NVlabs/denoising-diffusion-gan"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/learning-semantic-aligned-feature","slug":"learning-semantic-aligned-feature","title":"Learning Semantic-Aligned Feature Representation for Text-based Person Search","date":"2021-12-13","arxiv_id":"2112.06714","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/learning-semantic-aligned-feature#ran","syntology_url":"https://syntology.ai/paper/2112.06714","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.06714"}},"official":{"repos":["reallsp/SAF"],"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/nl-augmenter-a-framework-for-task-sensitive","slug":"nl-augmenter-a-framework-for-task-sensitive","title":"NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation","date":"2021-12-06","arxiv_id":"2112.02721","repositories_listed":2,"syntology":{"n":15,"n_ran":11,"n_constructed":0,"n_ran_checked":11,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":0,"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) · 4 unverified","sample_list":"/paper/nl-augmenter-a-framework-for-task-sensitive#ran","syntology_url":"https://syntology.ai/paper/2112.02721","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.02721"}},"official":{"repos":["GEM-benchmark/NL-Augmenter"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":4,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/make-it-move-controllable-image-to-video","slug":"make-it-move-controllable-image-to-video","title":"Make It Move: Controllable Image-to-Video Generation with Text Descriptions","date":"2021-12-06","arxiv_id":"2112.02815","repositories_listed":1,"syntology":{"n":13,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":6,"n_honours":0,"n_violates":3,"n_no_contract":3,"n_pointer_only":1,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 3 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/make-it-move-controllable-image-to-video#ran","syntology_url":"https://syntology.ai/paper/2112.02815","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.02815"}},"official":{"repos":["youncy-hu/mage"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/vortx-volumetric-3d-reconstruction-with","slug":"vortx-volumetric-3d-reconstruction-with","title":"VoRTX: Volumetric 3D Reconstruction With Transformers for Voxelwise View Selection and Fusion","date":"2021-12-01","arxiv_id":"2112.00236","repositories_listed":1,"syntology":{"n":13,"n_ran":11,"n_constructed":0,"n_ran_checked":11,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":10,"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) · 2 unverified","sample_list":"/paper/vortx-volumetric-3d-reconstruction-with#ran","syntology_url":"https://syntology.ai/paper/2112.00236","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.00236"}},"official":{"repos":["noahstier/vortx"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/smoothing-the-generative-latent-space-with","slug":"smoothing-the-generative-latent-space-with","title":"Few-shot Image Generation with Mixup-based Distance Learning","date":"2021-11-23","arxiv_id":"2111.11672","repositories_listed":3,"syntology":{"n":20,"n_ran":16,"n_constructed":0,"n_ran_checked":12,"n_instrument":4,"n_unverified":4,"n_honours":3,"n_violates":0,"n_no_contract":9,"n_pointer_only":11,"phrase":"16 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 3 honoured, 0 violated, 9 with no contract checked; 4 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/smoothing-the-generative-latent-space-with#ran","syntology_url":"https://syntology.ai/paper/2111.11672","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.11672"}},"official":{"repos":["reyllama/mixdl"],"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/scalable-diverse-model-selection-for","slug":"scalable-diverse-model-selection-for","title":"Scalable Diverse Model Selection for Accessible Transfer Learning","date":"2021-11-12","arxiv_id":"2111.06977","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":3,"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/scalable-diverse-model-selection-for#ran","syntology_url":"https://syntology.ai/paper/2111.06977","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.06977"}},"official":{"repos":["dbolya/parc"],"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/palette-image-to-image-diffusion-models-1","slug":"palette-image-to-image-diffusion-models-1","title":"Palette: Image-to-Image Diffusion Models","date":"2021-11-10","arxiv_id":"2111.05826","repositories_listed":5,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":1,"n_honours":1,"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; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/palette-image-to-image-diffusion-models-1#ran","syntology_url":"https://syntology.ai/paper/2111.05826","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.05826"}},"official":null}},{"url":"/paper/qimera-data-free-quantization-with-synthetic","slug":"qimera-data-free-quantization-with-synthetic","title":"Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples","date":"2021-11-04","arxiv_id":"2111.02625","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":2,"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/qimera-data-free-quantization-with-synthetic#ran","syntology_url":"https://syntology.ai/paper/2111.02625","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.02625"}},"official":{"repos":["iamkanghyunchoi/qimera"],"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":["listed","official"]}}},{"url":"/paper/improving-contrastive-learning-on-imbalanced","slug":"improving-contrastive-learning-on-imbalanced","title":"Improving Contrastive Learning on Imbalanced Seed Data via Open-World Sampling","date":"2021-11-01","arxiv_id":"2111.01004","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":0,"n_instrument":5,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":5,"phrase":"5 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; 5 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/improving-contrastive-learning-on-imbalanced#ran","syntology_url":"https://syntology.ai/paper/2111.01004","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.01004"}},"official":{"repos":["vita-group/mak"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/rebooting-acgan-auxiliary-classifier-gans","slug":"rebooting-acgan-auxiliary-classifier-gans","title":"Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training","date":"2021-11-01","arxiv_id":"2111.01118","repositories_listed":1,"syntology":{"n":9,"n_ran":9,"n_constructed":1,"n_ran_checked":2,"n_instrument":7,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":9,"phrase":"9 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; 7 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/rebooting-acgan-auxiliary-classifier-gans#ran","syntology_url":"https://syntology.ai/paper/2111.01118","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.01118"}},"official":{"repos":["POSTECH-CVLab/PyTorch-StudioGAN"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":1,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/diversity-matters-when-learning-from","slug":"diversity-matters-when-learning-from","title":"Diversity Matters When Learning From Ensembles","date":"2021-10-27","arxiv_id":"2110.14149","repositories_listed":0,"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/diversity-matters-when-learning-from#ran","syntology_url":"https://syntology.ai/paper/2110.14149","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.14149"}},"official":null}},{"url":"/paper/diversity-enhanced-active-learning-with","slug":"diversity-enhanced-active-learning-with","title":"Diversity Enhanced Active Learning with Strictly Proper Scoring Rules","date":"2021-10-27","arxiv_id":"2110.14171","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/diversity-enhanced-active-learning-with#ran","syntology_url":"https://syntology.ai/paper/2110.14171","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.14171"}},"official":{"repos":["davidtw999/bemps"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/augmax-adversarial-composition-of-random","slug":"augmax-adversarial-composition-of-random","title":"AugMax: Adversarial Composition of Random Augmentations for Robust Training","date":"2021-10-26","arxiv_id":"2110.13771","repositories_listed":1,"syntology":{"n":19,"n_ran":14,"n_constructed":0,"n_ran_checked":13,"n_instrument":1,"n_unverified":5,"n_honours":2,"n_violates":2,"n_no_contract":9,"n_pointer_only":0,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 13 with no instrument failure: 2 honoured, 2 violated, 9 with no contract checked; 1 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/augmax-adversarial-composition-of-random#ran","syntology_url":"https://syntology.ai/paper/2110.13771","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.13771"}},"official":{"repos":["vita-group/augmax"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":13,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/robustness-of-graph-neural-networks-at-scale","slug":"robustness-of-graph-neural-networks-at-scale","title":"Robustness of Graph Neural Networks at Scale","date":"2021-10-26","arxiv_id":"2110.14038","repositories_listed":2,"syntology":{"n":20,"n_ran":19,"n_constructed":0,"n_ran_checked":17,"n_instrument":2,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":16,"n_pointer_only":3,"phrase":"19 ran (of which 0 constructed an object rather than computing a result; 17 with no instrument failure: 1 honoured, 0 violated, 16 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/robustness-of-graph-neural-networks-at-scale#ran","syntology_url":"https://syntology.ai/paper/2110.14038","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.14038"}},"official":{"repos":["sigeisler/robustness_of_gnns_at_scale"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/regularizing-variational-autoencoder-with","slug":"regularizing-variational-autoencoder-with","title":"Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness","date":"2021-10-24","arxiv_id":"2110.12381","repositories_listed":1,"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/regularizing-variational-autoencoder-with#ran","syntology_url":"https://syntology.ai/paper/2110.12381","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.12381"}},"official":{"repos":["smilesdzgk/du-vae"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/blendgan-implicitly-gan-blending-for","slug":"blendgan-implicitly-gan-blending-for","title":"BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation","date":"2021-10-22","arxiv_id":"2110.11728","repositories_listed":3,"syntology":{"n":21,"n_ran":19,"n_constructed":0,"n_ran_checked":13,"n_instrument":6,"n_unverified":2,"n_honours":0,"n_violates":1,"n_no_contract":12,"n_pointer_only":4,"phrase":"19 ran (of which 0 constructed an object rather than computing a result; 13 with no instrument failure: 0 honoured, 1 violated, 12 with no contract checked; 6 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/blendgan-implicitly-gan-blending-for#ran","syntology_url":"https://syntology.ai/paper/2110.11728","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.11728"}},"official":{"repos":["onion-liu/BlendGAN"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/trigger-hunting-with-a-topological-prior-for-1","slug":"trigger-hunting-with-a-topological-prior-for-1","title":"Trigger Hunting with a Topological Prior for Trojan Detection","date":"2021-10-15","arxiv_id":"2110.08335","repositories_listed":1,"syntology":{"n":10,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":7,"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) · 7 unverified","sample_list":"/paper/trigger-hunting-with-a-topological-prior-for-1#ran","syntology_url":"https://syntology.ai/paper/2110.08335","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.08335"}},"official":{"repos":["HuXiaoling/TopoTrigger"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":7,"ran_from_kinds":["official"]}}},{"url":"/paper/towards-document-level-paraphrase-generation","slug":"towards-document-level-paraphrase-generation","title":"Towards Document-Level Paraphrase Generation with Sentence Rewriting and Reordering","date":"2021-09-15","arxiv_id":"2109.07095","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":1,"n_ran_checked":5,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":1,"phrase":"6 ran (of which 1 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/towards-document-level-paraphrase-generation#ran","syntology_url":"https://syntology.ai/paper/2109.07095","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.07095"}},"official":{"repos":["l-zhe/corpg"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":1,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/phrase-bert-improved-phrase-embeddings-from","slug":"phrase-bert-improved-phrase-embeddings-from","title":"Phrase-BERT: Improved Phrase Embeddings from BERT with an Application to Corpus Exploration","date":"2021-09-13","arxiv_id":"2109.06304","repositories_listed":2,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":1,"n_honours":1,"n_violates":1,"n_no_contract":6,"n_pointer_only":2,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 1 honoured, 1 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/phrase-bert-improved-phrase-embeddings-from#ran","syntology_url":"https://syntology.ai/paper/2109.06304","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.06304"}},"official":{"repos":["sf-wa-326/phrase-bert-topic-model"],"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":["listed","official"]}}},{"url":"/paper/illuminating-diverse-neural-cellular-automata","slug":"illuminating-diverse-neural-cellular-automata","title":"Illuminating Diverse Neural Cellular Automata for Level Generation","date":"2021-09-12","arxiv_id":"2109.05489","repositories_listed":2,"syntology":{"n":13,"n_ran":11,"n_constructed":0,"n_ran_checked":9,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":0,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/illuminating-diverse-neural-cellular-automata#ran","syntology_url":"https://syntology.ai/paper/2109.05489","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.05489"}},"official":{"repos":["smearle/control-pcgrl"],"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":["listed","official"]}}},{"url":"/paper/neural-latents-benchmark-21-evaluating-latent","slug":"neural-latents-benchmark-21-evaluating-latent","title":"Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity","date":"2021-09-09","arxiv_id":"2109.04463","repositories_listed":2,"syntology":{"n":24,"n_ran":17,"n_constructed":0,"n_ran_checked":17,"n_instrument":0,"n_unverified":7,"n_honours":0,"n_violates":0,"n_no_contract":17,"n_pointer_only":3,"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) · 7 unverified","sample_list":"/paper/neural-latents-benchmark-21-evaluating-latent#ran","syntology_url":"https://syntology.ai/paper/2109.04463","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.04463"}},"official":{"repos":["neurallatents/nlb_tools"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":4,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/pushing-paraphrase-away-from-original","slug":"pushing-paraphrase-away-from-original","title":"Pushing Paraphrase Away from Original Sentence: A Multi-Round Paraphrase Generation Approach","date":"2021-09-04","arxiv_id":"2109.01862","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":3,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"4 ran (of which 3 constructed an object rather than computing a result; 4 with no instrument failure: 1 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/pushing-paraphrase-away-from-original#ran","syntology_url":"https://syntology.ai/paper/2109.01862","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.01862"}},"official":{"repos":["l-zhe/btmpg"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":3,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/plan-then-generate-controlled-data-to-text","slug":"plan-then-generate-controlled-data-to-text","title":"Plan-then-Generate: Controlled Data-to-Text Generation via Planning","date":"2021-08-31","arxiv_id":"2108.13740","repositories_listed":2,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/plan-then-generate-controlled-data-to-text#ran","syntology_url":"https://syntology.ai/paper/2108.13740","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.13740"}},"official":{"repos":["google-research-datasets/ToTTo","yxuansu/plangen"],"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/ap-10k-a-benchmark-for-animal-pose-estimation","slug":"ap-10k-a-benchmark-for-animal-pose-estimation","title":"AP-10K: A Benchmark for Animal Pose Estimation in the Wild","date":"2021-08-28","arxiv_id":"2108.12617","repositories_listed":5,"syntology":{"n":9,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":0,"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) · 0 unverified","sample_list":"/paper/ap-10k-a-benchmark-for-animal-pose-estimation#ran","syntology_url":"https://syntology.ai/paper/2108.12617","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.12617"}},"official":{"repos":["alexthebad/ap10k","AlexTheBad/AP-10K"],"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/latent-space-energy-based-model-of-symbol","slug":"latent-space-energy-based-model-of-symbol","title":"Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification","date":"2021-08-26","arxiv_id":"2108.11556","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":0,"n_honours":3,"n_violates":0,"n_no_contract":0,"n_pointer_only":4,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 3 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/latent-space-energy-based-model-of-symbol#ran","syntology_url":"https://syntology.ai/paper/2108.11556","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.11556"}},"official":{"repos":["bpucla/ibebm"],"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"]}}},{"url":"/paper/influence-selection-for-active-learning","slug":"influence-selection-for-active-learning","title":"Influence Selection for Active Learning","date":"2021-08-20","arxiv_id":"2108.09331","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/influence-selection-for-active-learning#ran","syntology_url":"https://syntology.ai/paper/2108.09331","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.09331"}},"official":{"repos":["dragonlzm/ISAL"],"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/generating-smooth-pose-sequences-for-diverse","slug":"generating-smooth-pose-sequences-for-diverse","title":"Generating Smooth Pose Sequences for Diverse Human Motion Prediction","date":"2021-08-19","arxiv_id":"2108.08422","repositories_listed":1,"syntology":{"n":7,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":3,"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) · 5 unverified","sample_list":"/paper/generating-smooth-pose-sequences-for-diverse#ran","syntology_url":"https://syntology.ai/paper/2108.08422","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.08422"}},"official":{"repos":["wei-mao-2019/gsps"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/an-extensible-benchmark-suite-for-learning-to","slug":"an-extensible-benchmark-suite-for-learning-to","title":"An Extensible Benchmark Suite for Learning to Simulate Physical Systems","date":"2021-08-09","arxiv_id":"2108.07799","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/an-extensible-benchmark-suite-for-learning-to#ran","syntology_url":"https://syntology.ai/paper/2108.07799","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.07799"}},"official":{"repos":["karlotness/nn-benchmark"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/idm-an-intermediate-domain-module-for-domain","slug":"idm-an-intermediate-domain-module-for-domain","title":"IDM: An Intermediate Domain Module for Domain Adaptive Person Re-ID","date":"2021-08-05","arxiv_id":"2108.02413","repositories_listed":3,"syntology":{"n":2,"n_ran":2,"n_constructed":2,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"2 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; every one of the 2 samples that ran constructed an object rather than computing a result","sample_list":"/paper/idm-an-intermediate-domain-module-for-domain#ran","syntology_url":"https://syntology.ai/paper/2108.02413","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.02413"}},"official":{"repos":["SikaStar/IDM"],"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/batch-active-learning-at-scale","slug":"batch-active-learning-at-scale","title":"Batch Active Learning at Scale","date":"2021-07-29","arxiv_id":"2107.14263","repositories_listed":1,"syntology":{"n":8,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":0,"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) · 0 unverified","sample_list":"/paper/batch-active-learning-at-scale#ran","syntology_url":"https://syntology.ai/paper/2107.14263","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.14263"}},"official":null}},{"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/cgans-with-auxiliary-discriminative","slug":"cgans-with-auxiliary-discriminative","title":"Conditional GANs with Auxiliary Discriminative Classifier","date":"2021-07-21","arxiv_id":"2107.10060","repositories_listed":2,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":2,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":6,"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) · 2 unverified","sample_list":"/paper/cgans-with-auxiliary-discriminative#ran","syntology_url":"https://syntology.ai/paper/2107.10060","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.10060"}},"official":{"repos":["houliangict/adcgan"],"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":["named_in_paper","official"]}}},{"url":"/paper/tailor-generating-and-perturbing-text-with","slug":"tailor-generating-and-perturbing-text-with","title":"Tailor: Generating and Perturbing Text with Semantic Controls","date":"2021-07-15","arxiv_id":"2107.07150","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/tailor-generating-and-perturbing-text-with#ran","syntology_url":"https://syntology.ai/paper/2107.07150","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.07150"}},"official":{"repos":["allenai/tailor"],"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/personalized-federated-learning-via","slug":"personalized-federated-learning-via","title":"Sparse Personalized Federated Learning","date":"2021-07-12","arxiv_id":"2107.05330","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/personalized-federated-learning-via#ran","syntology_url":"https://syntology.ai/paper/2107.05330","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.05330"}},"official":null}},{"url":"/paper/semi-supervised-learning-with-multi-head-co","slug":"semi-supervised-learning-with-multi-head-co","title":"Semi-Supervised Learning with Multi-Head Co-Training","date":"2021-07-10","arxiv_id":"2107.04795","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/semi-supervised-learning-with-multi-head-co#ran","syntology_url":"https://syntology.ai/paper/2107.04795","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.04795"}},"official":{"repos":["chenmc1996/Multi-Head-Co-Training"],"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/an-investigation-of-the-in-effectiveness-of","slug":"an-investigation-of-the-in-effectiveness-of","title":"An Investigation of the (In)effectiveness of Counterfactually Augmented Data","date":"2021-07-01","arxiv_id":"2107.00753","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/an-investigation-of-the-in-effectiveness-of#ran","syntology_url":"https://syntology.ai/paper/2107.00753","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.00753"}},"official":{"repos":["joshinh/investigation-cad"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/resvit-residual-vision-transformers-for-multi","slug":"resvit-residual-vision-transformers-for-multi","title":"ResViT: Residual vision transformers for multi-modal medical image synthesis","date":"2021-06-30","arxiv_id":"2106.16031","repositories_listed":2,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/resvit-residual-vision-transformers-for-multi#ran","syntology_url":"https://syntology.ai/paper/2106.16031","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.16031"}},"official":{"repos":["icon-lab/ResViT"],"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/umic-an-unreferenced-metric-for-image","slug":"umic-an-unreferenced-metric-for-image","title":"UMIC: An Unreferenced Metric for Image Captioning via Contrastive Learning","date":"2021-06-26","arxiv_id":"2106.14019","repositories_listed":1,"syntology":{"n":14,"n_ran":7,"n_constructed":4,"n_ran_checked":7,"n_instrument":0,"n_unverified":7,"n_honours":1,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"7 ran (of which 4 constructed an object rather than computing a result; 7 with no instrument failure: 1 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/umic-an-unreferenced-metric-for-image#ran","syntology_url":"https://syntology.ai/paper/2106.14019","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.14019"}},"official":{"repos":["hwanheelee1993/UMIC"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":4,"n_ran_no_instrument_failure":7,"n_unverified":7,"ran_from_kinds":["official"]}}},{"url":"/paper/very-deep-graph-neural-networks-via-noise","slug":"very-deep-graph-neural-networks-via-noise","title":"Simple GNN Regularisation for 3D Molecular Property Prediction & Beyond","date":"2021-06-15","arxiv_id":"2106.07971","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/very-deep-graph-neural-networks-via-noise#ran","syntology_url":"https://syntology.ai/paper/2106.07971","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.07971"}},"official":null}},{"url":"/paper/learning-to-see-by-looking-at-noise","slug":"learning-to-see-by-looking-at-noise","title":"Learning to See by Looking at Noise","date":"2021-06-10","arxiv_id":"2106.05963","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/learning-to-see-by-looking-at-noise#ran","syntology_url":"https://syntology.ai/paper/2106.05963","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.05963"}},"official":{"repos":["mbaradad/learning_with_noise"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/refiner-refining-self-attention-for-vision","slug":"refiner-refining-self-attention-for-vision","title":"Refiner: Refining Self-attention for Vision Transformers","date":"2021-06-07","arxiv_id":"2106.03714","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/refiner-refining-self-attention-for-vision#ran","syntology_url":"https://syntology.ai/paper/2106.03714","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.03714"}},"official":{"repos":["zhoudaquan/Refiner_ViT"],"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/differentiable-quality-diversity","slug":"differentiable-quality-diversity","title":"Differentiable Quality Diversity","date":"2021-06-07","arxiv_id":"2106.03894","repositories_listed":3,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":0,"n_instrument":4,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":5,"phrase":"4 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; 4 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/differentiable-quality-diversity#ran","syntology_url":"https://syntology.ai/paper/2106.03894","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.03894"}},"official":{"repos":["icaros-usc/dqd","icaros-usc/pyribs"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/eventdrop-data-augmentation-for-event-based","slug":"eventdrop-data-augmentation-for-event-based","title":"EventDrop: data augmentation for event-based learning","date":"2021-06-07","arxiv_id":"2106.05836","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/eventdrop-data-augmentation-for-event-based#ran","syntology_url":"https://syntology.ai/paper/2106.05836","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.05836"}},"official":{"repos":["fuqianggu/EventDrop"],"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/preferencenet-encoding-human-preferences-in","slug":"preferencenet-encoding-human-preferences-in","title":"PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning","date":"2021-06-06","arxiv_id":"2106.03215","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":3,"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/preferencenet-encoding-human-preferences-in#ran","syntology_url":"https://syntology.ai/paper/2106.03215","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.03215"}},"official":{"repos":["neeharperi/PreferenceNet"],"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/meta-learning-with-variational-semantic","slug":"meta-learning-with-variational-semantic","title":"Meta-Learning with Variational Semantic Memory for Word Sense Disambiguation","date":"2021-06-05","arxiv_id":"2106.02960","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":4,"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 4 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; every one of the 4 samples that ran constructed an object rather than computing a result","sample_list":"/paper/meta-learning-with-variational-semantic#ran","syntology_url":"https://syntology.ai/paper/2106.02960","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.02960"}},"official":{"repos":["YDU-uva/VSM_WSD"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":4,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/generate-prune-select-a-pipeline-for","slug":"generate-prune-select-a-pipeline-for","title":"Generate, Prune, Select: A Pipeline for Counterspeech Generation against Online Hate Speech","date":"2021-06-03","arxiv_id":"2106.01625","repositories_listed":1,"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":0,"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/generate-prune-select-a-pipeline-for#ran","syntology_url":"https://syntology.ai/paper/2106.01625","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.01625"}},"official":{"repos":["WanzhengZhu/GPS"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/snips-solving-noisy-inverse-problems","slug":"snips-solving-noisy-inverse-problems","title":"SNIPS: Solving Noisy Inverse Problems Stochastically","date":"2021-05-31","arxiv_id":"2105.14951","repositories_listed":1,"syntology":{"n":22,"n_ran":12,"n_constructed":5,"n_ran_checked":6,"n_instrument":6,"n_unverified":10,"n_honours":1,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"12 ran (of which 5 constructed an object rather than computing a result; 6 with no instrument failure: 1 honoured, 0 violated, 5 with no contract checked; 6 where Syntology's instrument failed) · 10 unverified","sample_list":"/paper/snips-solving-noisy-inverse-problems#ran","syntology_url":"https://syntology.ai/paper/2105.14951","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.14951"}},"official":{"repos":["bahjat-kawar/snips_torch"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":5,"n_ran_no_instrument_failure":6,"n_unverified":10,"ran_from_kinds":["official"]}}},{"url":"/paper/towards-diverse-paragraph-captioning-for","slug":"towards-diverse-paragraph-captioning-for","title":"Towards Diverse Paragraph Captioning for Untrimmed Videos","date":"2021-05-30","arxiv_id":"2105.14477","repositories_listed":1,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":4,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":2,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/towards-diverse-paragraph-captioning-for#ran","syntology_url":"https://syntology.ai/paper/2105.14477","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.14477"}},"official":{"repos":["syuqings/video-paragraph"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/diversifying-dialog-generation-via-adaptive","slug":"diversifying-dialog-generation-via-adaptive","title":"Diversifying Dialog Generation via Adaptive Label Smoothing","date":"2021-05-30","arxiv_id":"2105.14556","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":2,"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 2 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/diversifying-dialog-generation-via-adaptive#ran","syntology_url":"https://syntology.ai/paper/2105.14556","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.14556"}},"official":{"repos":["lemon234071/AdaLabel"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/transforming-the-latent-space-of-stylegan-for","slug":"transforming-the-latent-space-of-stylegan-for","title":"Transforming the Latent Space of StyleGAN for Real Face Editing","date":"2021-05-29","arxiv_id":"2105.14230","repositories_listed":1,"syntology":{"n":13,"n_ran":10,"n_constructed":0,"n_ran_checked":8,"n_instrument":2,"n_unverified":3,"n_honours":2,"n_violates":1,"n_no_contract":5,"n_pointer_only":2,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 2 honoured, 1 violated, 5 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/transforming-the-latent-space-of-stylegan-for#ran","syntology_url":"https://syntology.ai/paper/2105.14230","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.14230"}},"official":{"repos":["AnonSubm2021/TransStyleGAN"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/rest-an-efficient-transformer-for-visual","slug":"rest-an-efficient-transformer-for-visual","title":"ResT: An Efficient Transformer for Visual Recognition","date":"2021-05-28","arxiv_id":"2105.13677","repositories_listed":5,"syntology":{"n":9,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":9,"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) · 0 unverified","sample_list":"/paper/rest-an-efficient-transformer-for-visual#ran","syntology_url":"https://syntology.ai/paper/2105.13677","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.13677"}},"official":{"repos":["wofmanaf/ResT"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/protaugment-unsupervised-diverse-short-texts","slug":"protaugment-unsupervised-diverse-short-texts","title":"ProtAugment: Unsupervised diverse short-texts paraphrasing for intent detection meta-learning","date":"2021-05-27","arxiv_id":"2105.12995","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":1,"n_instrument":3,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"4 ran (of which 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) · 2 unverified","sample_list":"/paper/protaugment-unsupervised-diverse-short-texts#ran","syntology_url":"https://syntology.ai/paper/2105.12995","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.12995"}},"official":{"repos":["tdopierre/ProtAugment"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/project-codenet-a-large-scale-ai-for-code","slug":"project-codenet-a-large-scale-ai-for-code","title":"CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks","date":"2021-05-25","arxiv_id":"2105.12655","repositories_listed":1,"syntology":{"n":9,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/project-codenet-a-large-scale-ai-for-code#ran","syntology_url":"https://syntology.ai/paper/2105.12655","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.12655"}},"official":{"repos":["IBM/Project_CodeNet"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/an-empirical-study-of-vehicle-re","slug":"an-empirical-study-of-vehicle-re","title":"An Empirical Study of Vehicle Re-Identification on the AI City Challenge","date":"2021-05-20","arxiv_id":"2105.09701","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":2,"phrase":"4 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; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/an-empirical-study-of-vehicle-re#ran","syntology_url":"https://syntology.ai/paper/2105.09701","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.09701"}},"official":{"repos":["michuanhaohao/AICITY2021_Track2_DMT"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/mapgo-model-assisted-policy-optimization-for","slug":"mapgo-model-assisted-policy-optimization-for","title":"MapGo: Model-Assisted Policy Optimization for Goal-Oriented Tasks","date":"2021-05-13","arxiv_id":"2105.06350","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/mapgo-model-assisted-policy-optimization-for#ran","syntology_url":"https://syntology.ai/paper/2105.06350","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.06350"}},"official":{"repos":["apexrl/MapGo"],"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/diffusion-models-beat-gans-on-image-synthesis","slug":"diffusion-models-beat-gans-on-image-synthesis","title":"Diffusion Models Beat GANs on Image Synthesis","date":"2021-05-11","arxiv_id":"2105.05233","repositories_listed":21,"syntology":{"n":50,"n_ran":33,"n_constructed":13,"n_ran_checked":29,"n_instrument":4,"n_unverified":17,"n_honours":4,"n_violates":0,"n_no_contract":25,"n_pointer_only":19,"phrase":"33 ran (of which 13 constructed an object rather than computing a result; 29 with no instrument failure: 4 honoured, 0 violated, 25 with no contract checked; 4 where Syntology's instrument failed) · 17 unverified","sample_list":"/paper/diffusion-models-beat-gans-on-image-synthesis#ran","syntology_url":"https://syntology.ai/paper/2105.05233","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.05233"}},"official":{"repos":["openai/guided-diffusion"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}}],"record_sha256":"53c993d1ba8832aebbb4bc284fb641a753df454115229271d8e4e44aa6ec1151","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}