{"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/prediction/papers/ran/3","list_of":"/task/prediction","task":"Prediction","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":3,"pages_in_order":7,"rows_per_page":100,"rows":[201,300],"of":607,"counts":{"archive_papers_tagged":8760,"with_a_code_link":2835,"where_syntology_ran_a_sample":607,"not_listed_spam_title":0,"listed":8760,"listed_where_code_ran":607,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":519,"every_run_a_failure_of_syntologys_instrument":88,"listed_with_a_run_with_no_instrument_failure":519,"listed_every_run_a_failure_of_syntologys_instrument":88,"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/prediction/papers/ran/1","prev":"/task/prediction/papers/ran/2","next":"/task/prediction/papers/ran/4","papers":[{"url":"/paper/taskmet-task-driven-metric-learning-for-model-1","slug":"taskmet-task-driven-metric-learning-for-model-1","title":"TaskMet: Task-Driven Metric Learning for Model Learning","date":"2023-12-08","arxiv_id":"2312.05250","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/taskmet-task-driven-metric-learning-for-model-1#ran","syntology_url":"https://syntology.ai/paper/2312.05250","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2312.05250"}},"official":{"repos":["facebookresearch/taskmet"],"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/predicting-and-interpreting-energy-barriers","slug":"predicting-and-interpreting-energy-barriers","title":"Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks","date":"2023-12-08","arxiv_id":"2401.08627","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":2,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":2,"phrase":"2 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; every one of the 2 samples that ran constructed an object rather than computing a result","sample_list":"/paper/predicting-and-interpreting-energy-barriers#ran","syntology_url":"https://syntology.ai/paper/2401.08627","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.08627"}},"official":{"repos":["haoyuli02/symgnn"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/provable-adversarial-robustness-for-group-1","slug":"provable-adversarial-robustness-for-group-1","title":"Provable Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More","date":"2023-12-05","arxiv_id":"2312.02708","repositories_listed":0,"syntology":{"n":31,"n_ran":22,"n_constructed":1,"n_ran_checked":19,"n_instrument":3,"n_unverified":9,"n_honours":0,"n_violates":0,"n_no_contract":19,"n_pointer_only":4,"phrase":"22 ran (of which 1 constructed an object rather than computing a result; 19 with no instrument failure: 0 honoured, 0 violated, 19 with no contract checked; 3 where Syntology's instrument failed) · 9 unverified","sample_list":"/paper/provable-adversarial-robustness-for-group-1#ran","syntology_url":"https://syntology.ai/paper/2312.02708","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2312.02708"}},"official":null}},{"url":"/paper/explaining-with-contrastive-phrasal","slug":"explaining-with-contrastive-phrasal","title":"Explaining with Contrastive Phrasal Highlighting: A Case Study in Assisting Humans to Detect Translation Differences","date":"2023-12-04","arxiv_id":"2312.01582","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/explaining-with-contrastive-phrasal#ran","syntology_url":"https://syntology.ai/paper/2312.01582","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2312.01582"}},"official":{"repos":["elbria/ex-semdiv"],"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/exploiting-diffusion-prior-for-generalizable","slug":"exploiting-diffusion-prior-for-generalizable","title":"Exploiting Diffusion Prior for Generalizable Dense Prediction","date":"2023-11-30","arxiv_id":"2311.18832","repositories_listed":2,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":3,"n_pointer_only":2,"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/exploiting-diffusion-prior-for-generalizable#ran","syntology_url":"https://syntology.ai/paper/2311.18832","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.18832"}},"official":{"repos":["shinying/dmp"],"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/precipitation-prediction-using-an-ensemble-of","slug":"precipitation-prediction-using-an-ensemble-of","title":"Precipitation Prediction Using an Ensemble of Lightweight Learners","date":"2023-11-30","arxiv_id":"2401.09424","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":5,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/precipitation-prediction-using-an-ensemble-of#ran","syntology_url":"https://syntology.ai/paper/2401.09424","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.09424"}},"official":{"repos":["lxz1217/weather4cast-2023-lxz"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/cam4docc-benchmark-for-camera-only-4d","slug":"cam4docc-benchmark-for-camera-only-4d","title":"Cam4DOcc: Benchmark for Camera-Only 4D Occupancy Forecasting in Autonomous Driving Applications","date":"2023-11-29","arxiv_id":"2311.17663","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/cam4docc-benchmark-for-camera-only-4d#ran","syntology_url":"https://syntology.ai/paper/2311.17663","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.17663"}},"official":{"repos":["haomo-ai/cam4docc"],"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/typhoon-intensity-prediction-with-vision","slug":"typhoon-intensity-prediction-with-vision","title":"Typhoon Intensity Prediction with Vision Transformer","date":"2023-11-28","arxiv_id":"2311.16450","repositories_listed":1,"syntology":{"n":12,"n_ran":10,"n_constructed":0,"n_ran_checked":7,"n_instrument":3,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":12,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/typhoon-intensity-prediction-with-vision#ran","syntology_url":"https://syntology.ai/paper/2311.16450","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.16450"}},"official":{"repos":["chen-huanxin/tint"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/selfocc-self-supervised-vision-based-3d","slug":"selfocc-self-supervised-vision-based-3d","title":"SelfOcc: Self-Supervised Vision-Based 3D Occupancy Prediction","date":"2023-11-21","arxiv_id":"2311.12754","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/selfocc-self-supervised-vision-based-3d#ran","syntology_url":"https://syntology.ai/paper/2311.12754","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.12754"}},"official":{"repos":["huang-yh/selfocc"],"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/kandinsky-conformal-prediction-efficient","slug":"kandinsky-conformal-prediction-efficient","title":"Kandinsky Conformal Prediction: Efficient Calibration of Image Segmentation Algorithms","date":"2023-11-20","arxiv_id":"2311.11837","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/kandinsky-conformal-prediction-efficient#ran","syntology_url":"https://syntology.ai/paper/2311.11837","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.11837"}},"official":{"repos":["NKI-AI/kandinsky-calibration"],"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/lepard-a-large-scale-dataset-of-judges-citing","slug":"lepard-a-large-scale-dataset-of-judges-citing","title":"LePaRD: A Large-Scale Dataset of Judges Citing Precedents","date":"2023-11-15","arxiv_id":"2311.09356","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":9,"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/lepard-a-large-scale-dataset-of-judges-citing#ran","syntology_url":"https://syntology.ai/paper/2311.09356","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.09356"}},"official":{"repos":["rmahari/lepard"],"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/polymax-general-dense-prediction-with-mask","slug":"polymax-general-dense-prediction-with-mask","title":"PolyMaX: General Dense Prediction with Mask Transformer","date":"2023-11-09","arxiv_id":"2311.05770","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/polymax-general-dense-prediction-with-mask#ran","syntology_url":"https://syntology.ai/paper/2311.05770","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.05770"}},"official":{"repos":["google-research/deeplab2"],"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/combating-bilateral-edge-noise-for-robust-1","slug":"combating-bilateral-edge-noise-for-robust-1","title":"Combating Bilateral Edge Noise for Robust Link Prediction","date":"2023-11-02","arxiv_id":"2311.01196","repositories_listed":1,"syntology":{"n":34,"n_ran":20,"n_constructed":2,"n_ran_checked":16,"n_instrument":4,"n_unverified":14,"n_honours":2,"n_violates":1,"n_no_contract":13,"n_pointer_only":19,"phrase":"20 ran (of which 2 constructed an object rather than computing a result; 16 with no instrument failure: 2 honoured, 1 violated, 13 with no contract checked; 4 where Syntology's instrument failed) · 14 unverified","sample_list":"/paper/combating-bilateral-edge-noise-for-robust-1#ran","syntology_url":"https://syntology.ai/paper/2311.01196","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.01196"}},"official":{"repos":["tmlr-group/rgib"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":4,"ran_from_kinds":["found_in_text","official"]}}},{"url":"/paper/ppi-efficient-prediction-powered-inference","slug":"ppi-efficient-prediction-powered-inference","title":"PPI++: Efficient Prediction-Powered Inference","date":"2023-11-02","arxiv_id":"2311.01453","repositories_listed":2,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/ppi-efficient-prediction-powered-inference#ran","syntology_url":"https://syntology.ai/paper/2311.01453","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.01453"}},"official":{"repos":["aangelopoulos/ppi_py"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/interpretable-prototype-based-graph-1","slug":"interpretable-prototype-based-graph-1","title":"Interpretable Prototype-based Graph Information Bottleneck","date":"2023-10-30","arxiv_id":"2310.19906","repositories_listed":1,"syntology":{"n":49,"n_ran":27,"n_constructed":8,"n_ran_checked":12,"n_instrument":15,"n_unverified":22,"n_honours":3,"n_violates":0,"n_no_contract":9,"n_pointer_only":48,"phrase":"27 ran (of which 8 constructed an object rather than computing a result; 12 with no instrument failure: 3 honoured, 0 violated, 9 with no contract checked; 15 where Syntology's instrument failed) · 22 unverified","sample_list":"/paper/interpretable-prototype-based-graph-1#ran","syntology_url":"https://syntology.ai/paper/2310.19906","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.19906"}},"official":{"repos":["sang-woo-seo/pgib"],"state":"official (archive's flag): 25 ran","n_ran":25,"n_constructed":8,"n_ran_no_instrument_failure":11,"n_unverified":22,"ran_from_kinds":["community","official","unlocated"]}}},{"url":"/paper/neuro-inspired-fragmentation-and-recall-to","slug":"neuro-inspired-fragmentation-and-recall-to","title":"Neuro-Inspired Fragmentation and Recall to Overcome Catastrophic Forgetting in Curiosity","date":"2023-10-26","arxiv_id":"2310.17537","repositories_listed":1,"syntology":{"n":6,"n_ran":5,"n_constructed":4,"n_ran_checked":5,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 4 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/neuro-inspired-fragmentation-and-recall-to#ran","syntology_url":"https://syntology.ai/paper/2310.17537","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.17537"}},"official":{"repos":["fietelab/farcuriosity"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":4,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/a-boundary-offset-prediction-network-for","slug":"a-boundary-offset-prediction-network-for","title":"A Boundary Offset Prediction Network for Named Entity Recognition","date":"2023-10-23","arxiv_id":"2310.18349","repositories_listed":1,"syntology":{"n":7,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":7,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/a-boundary-offset-prediction-network-for#ran","syntology_url":"https://syntology.ai/paper/2310.18349","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.18349"}},"official":{"repos":["mhtang1995/bopn"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/counterfactual-prediction-under-selective","slug":"counterfactual-prediction-under-selective","title":"Counterfactual Prediction Under Selective Confounding","date":"2023-10-21","arxiv_id":"2310.14064","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":4,"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/counterfactual-prediction-under-selective#ran","syntology_url":"https://syntology.ai/paper/2310.14064","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.14064"}},"official":{"repos":["sohaib730/causalml"],"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/relm-leveraging-language-models-for-enhanced","slug":"relm-leveraging-language-models-for-enhanced","title":"ReLM: Leveraging Language Models for Enhanced Chemical Reaction Prediction","date":"2023-10-20","arxiv_id":"2310.13590","repositories_listed":1,"syntology":{"n":11,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":1,"n_no_contract":7,"n_pointer_only":11,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 1 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/relm-leveraging-language-models-for-enhanced#ran","syntology_url":"https://syntology.ai/paper/2310.13590","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.13590"}},"official":{"repos":["syr-cn/relm"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/improving-molecular-properties-prediction","slug":"improving-molecular-properties-prediction","title":"Improving Molecular Properties Prediction Through Latent Space Fusion","date":"2023-10-20","arxiv_id":"2310.13802","repositories_listed":1,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":4,"n_pointer_only":1,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/improving-molecular-properties-prediction#ran","syntology_url":"https://syntology.ai/paper/2310.13802","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.13802"}},"official":{"repos":["ibm/molformer"],"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/conformal-prediction-for-deep-classifier-via","slug":"conformal-prediction-for-deep-classifier-via","title":"Conformal Prediction for Deep Classifier via Label Ranking","date":"2023-10-10","arxiv_id":"2310.06430","repositories_listed":3,"syntology":{"n":15,"n_ran":10,"n_constructed":1,"n_ran_checked":9,"n_instrument":1,"n_unverified":5,"n_honours":1,"n_violates":0,"n_no_contract":8,"n_pointer_only":15,"phrase":"10 ran (of which 1 constructed an object rather than computing a result; 9 with no instrument failure: 1 honoured, 0 violated, 8 with no contract checked; 1 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/conformal-prediction-for-deep-classifier-via#ran","syntology_url":"https://syntology.ai/paper/2310.06430","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.06430"}},"official":{"repos":["ml-stat-Sustech/conformal_prediction_via_label_ranking"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/asymptotically-free-sketched-ridge-ensembles","slug":"asymptotically-free-sketched-ridge-ensembles","title":"Asymptotically free sketched ridge ensembles: Risks, cross-validation, and tuning","date":"2023-10-06","arxiv_id":"2310.04357","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/asymptotically-free-sketched-ridge-ensembles#ran","syntology_url":"https://syntology.ai/paper/2310.04357","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.04357"}},"official":{"repos":["dlej/sketched-ridge"],"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/towards-out-of-distribution-generalizable","slug":"towards-out-of-distribution-generalizable","title":"Towards out-of-distribution generalizable predictions of chemical kinetics properties","date":"2023-10-04","arxiv_id":"2310.03152","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":4,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":6,"phrase":"6 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; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/towards-out-of-distribution-generalizable#ran","syntology_url":"https://syntology.ai/paper/2310.03152","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.03152"}},"official":{"repos":["zihao-wang/reactionood"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/clipself-vision-transformer-distills-itself","slug":"clipself-vision-transformer-distills-itself","title":"CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction","date":"2023-10-02","arxiv_id":"2310.01403","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":6,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/clipself-vision-transformer-distills-itself#ran","syntology_url":"https://syntology.ai/paper/2310.01403","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.01403"}},"official":{"repos":["wusize/clipself"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/revisiting-link-prediction-a-data-perspective","slug":"revisiting-link-prediction-a-data-perspective","title":"Revisiting Link Prediction: A Data Perspective","date":"2023-10-01","arxiv_id":"2310.00793","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/revisiting-link-prediction-a-data-perspective#ran","syntology_url":"https://syntology.ai/paper/2310.00793","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.00793"}},"official":{"repos":["juanhui28/heart"],"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/robots-that-can-see-leveraging-human-pose-for","slug":"robots-that-can-see-leveraging-human-pose-for","title":"Robots That Can See: Leveraging Human Pose for Trajectory Prediction","date":"2023-09-29","arxiv_id":"2309.17209","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/robots-that-can-see-leveraging-human-pose-for#ran","syntology_url":"https://syntology.ai/paper/2309.17209","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.17209"}},"official":{"repos":["google-research/human-scene-transformer"],"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/networked-inequality-preferential-attachment","slug":"networked-inequality-preferential-attachment","title":"Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction","date":"2023-09-29","arxiv_id":"2309.17417","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/networked-inequality-preferential-attachment#ran","syntology_url":"https://syntology.ai/paper/2309.17417","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.17417"}},"official":{"repos":["arjunsubramonian/link_bias_amplification"],"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/cross-prediction-powered-inference","slug":"cross-prediction-powered-inference","title":"Cross-Prediction-Powered Inference","date":"2023-09-28","arxiv_id":"2309.16598","repositories_listed":2,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/cross-prediction-powered-inference#ran","syntology_url":"https://syntology.ai/paper/2309.16598","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.16598"}},"official":{"repos":["tijana-zrnic/cross-ppi"],"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/node-aligned-graph-to-graph-generation-for","slug":"node-aligned-graph-to-graph-generation-for","title":"Node-Aligned Graph-to-Graph (NAG2G): Elevating Template-Free Deep Learning Approaches in Single-Step Retrosynthesis","date":"2023-09-27","arxiv_id":"2309.15798","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/node-aligned-graph-to-graph-generation-for#ran","syntology_url":"https://syntology.ai/paper/2309.15798","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.15798"}},"official":{"repos":["dptech-corp/nag2g"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/class-incremental-learning-via-likelihood","slug":"class-incremental-learning-via-likelihood","title":"Class Incremental Learning via Likelihood Ratio Based Task Prediction","date":"2023-09-26","arxiv_id":"2309.15048","repositories_listed":2,"syntology":{"n":11,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":11,"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) · 4 unverified","sample_list":"/paper/class-incremental-learning-via-likelihood#ran","syntology_url":"https://syntology.ai/paper/2309.15048","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.15048"}},"official":{"repos":["linhaowei1/tpl","linhaowei1/tplr"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/a-spectral-theory-of-neural-prediction-and","slug":"a-spectral-theory-of-neural-prediction-and","title":"A Spectral Theory of Neural Prediction and Alignment","date":"2023-09-22","arxiv_id":"2309.12821","repositories_listed":1,"syntology":{"n":23,"n_ran":11,"n_constructed":0,"n_ran_checked":9,"n_instrument":2,"n_unverified":12,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":2,"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) · 12 unverified","sample_list":"/paper/a-spectral-theory-of-neural-prediction-and#ran","syntology_url":"https://syntology.ai/paper/2309.12821","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.12821"}},"official":{"repos":["chung-neuroai-lab/snap"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":12,"ran_from_kinds":["official"]}}},{"url":"/paper/contextual-label-projection-for-cross-lingual","slug":"contextual-label-projection-for-cross-lingual","title":"Contextual Label Projection for Cross-Lingual Structured Prediction","date":"2023-09-16","arxiv_id":"2309.08943","repositories_listed":1,"syntology":{"n":15,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":15,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/contextual-label-projection-for-cross-lingual#ran","syntology_url":"https://syntology.ai/paper/2309.08943","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.08943"}},"official":{"repos":["pluslabnlp/clap"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/pure-message-passing-can-estimate-common","slug":"pure-message-passing-can-estimate-common","title":"Pure Message Passing Can Estimate Common Neighbor for Link Prediction","date":"2023-09-02","arxiv_id":"2309.00976","repositories_listed":1,"syntology":{"n":10,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":10,"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) · 2 unverified","sample_list":"/paper/pure-message-passing-can-estimate-common#ran","syntology_url":"https://syntology.ai/paper/2309.00976","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.00976"}},"official":{"repos":["Barcavin/efficient-node-labelling"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/where-would-i-go-next-large-language-models","slug":"where-would-i-go-next-large-language-models","title":"Where Would I Go Next? Large Language Models as Human Mobility Predictors","date":"2023-08-29","arxiv_id":"2308.15197","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/where-would-i-go-next-large-language-models#ran","syntology_url":"https://syntology.ai/paper/2308.15197","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.15197"}},"official":{"repos":["xlwang233/llm-mob"],"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/tpugraphs-a-performance-prediction-dataset-on-1","slug":"tpugraphs-a-performance-prediction-dataset-on-1","title":"TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs","date":"2023-08-25","arxiv_id":"2308.13490","repositories_listed":1,"syntology":{"n":4,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/tpugraphs-a-performance-prediction-dataset-on-1#ran","syntology_url":"https://syntology.ai/paper/2308.13490","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.13490"}},"official":{"repos":["google-research-datasets/tpu_graphs"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/swinlstm-improving-spatiotemporal-prediction","slug":"swinlstm-improving-spatiotemporal-prediction","title":"SwinLSTM:Improving Spatiotemporal Prediction Accuracy using Swin Transformer and LSTM","date":"2023-08-19","arxiv_id":"2308.09891","repositories_listed":1,"syntology":{"n":9,"n_ran":4,"n_constructed":4,"n_ran_checked":4,"n_instrument":0,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 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) · 5 unverified; every one of the 4 samples that ran constructed an object rather than computing a result","sample_list":"/paper/swinlstm-improving-spatiotemporal-prediction#ran","syntology_url":"https://syntology.ai/paper/2308.09891","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.09891"}},"official":{"repos":["SongTang-x/SwinLSTM"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":4,"n_ran_no_instrument_failure":4,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/diffusion-variational-autoencoder-for","slug":"diffusion-variational-autoencoder-for","title":"Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction","date":"2023-08-18","arxiv_id":"2309.00073","repositories_listed":1,"syntology":{"n":14,"n_ran":11,"n_constructed":0,"n_ran_checked":9,"n_instrument":2,"n_unverified":3,"n_honours":2,"n_violates":0,"n_no_contract":7,"n_pointer_only":14,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 2 honoured, 0 violated, 7 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/diffusion-variational-autoencoder-for#ran","syntology_url":"https://syntology.ai/paper/2309.00073","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.00073"}},"official":{"repos":["koa-fin/dva"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/fast-inference-and-update-of-probabilistic","slug":"fast-inference-and-update-of-probabilistic","title":"Fast Inference and Update of Probabilistic Density Estimation on Trajectory Prediction","date":"2023-08-17","arxiv_id":"2308.08824","repositories_listed":1,"syntology":{"n":11,"n_ran":8,"n_constructed":0,"n_ran_checked":7,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":11,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/fast-inference-and-update-of-probabilistic#ran","syntology_url":"https://syntology.ai/paper/2308.08824","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.08824"}},"official":{"repos":["meaten/flowchain-iccv2023"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/temporal-interest-network-for-click-through","slug":"temporal-interest-network-for-click-through","title":"Temporal Interest Network for User Response Prediction","date":"2023-08-15","arxiv_id":"2308.08487","repositories_listed":2,"syntology":{"n":7,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":7,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/temporal-interest-network-for-click-through#ran","syntology_url":"https://syntology.ai/paper/2308.08487","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.08487"}},"official":{"repos":["zhouxy1003/tin"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/precipitation-nowcasting-with-generative","slug":"precipitation-nowcasting-with-generative","title":"Precipitation nowcasting with generative diffusion models","date":"2023-08-13","arxiv_id":"2308.06733","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":6,"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/precipitation-nowcasting-with-generative#ran","syntology_url":"https://syntology.ai/paper/2308.06733","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.06733"}},"official":{"repos":["fmerizzi/precipitation-nowcasting-with-generative-diffusion-models"],"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/joint-relation-transformer-for-multi-person","slug":"joint-relation-transformer-for-multi-person","title":"Joint-Relation Transformer for Multi-Person Motion Prediction","date":"2023-08-09","arxiv_id":"2308.04808","repositories_listed":1,"syntology":{"n":21,"n_ran":18,"n_constructed":0,"n_ran_checked":17,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":17,"n_pointer_only":21,"phrase":"18 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; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/joint-relation-transformer-for-multi-person#ran","syntology_url":"https://syntology.ai/paper/2308.04808","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.04808"}},"official":{"repos":["mediabrain-sjtu/jrtransformer"],"state":"official (archive's flag): 18 ran","n_ran":18,"n_constructed":0,"n_ran_no_instrument_failure":17,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/map-a-model-agnostic-pretraining-framework","slug":"map-a-model-agnostic-pretraining-framework","title":"MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction","date":"2023-08-03","arxiv_id":"2308.01737","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/map-a-model-agnostic-pretraining-framework#ran","syntology_url":"https://syntology.ai/paper/2308.01737","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.01737"}},"official":{"repos":["chiangel/map-code"],"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/conformal-pid-control-for-time-series-1","slug":"conformal-pid-control-for-time-series-1","title":"Conformal PID Control for Time Series Prediction","date":"2023-07-31","arxiv_id":"2307.16895","repositories_listed":1,"syntology":{"n":10,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/conformal-pid-control-for-time-series-1#ran","syntology_url":"https://syntology.ai/paper/2307.16895","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.16895"}},"official":{"repos":["aangelopoulos/conformal-time-series"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/crystal-structure-prediction-by-joint-1","slug":"crystal-structure-prediction-by-joint-1","title":"Crystal Structure Prediction by Joint Equivariant Diffusion","date":"2023-07-30","arxiv_id":"2309.04475","repositories_listed":2,"syntology":{"n":7,"n_ran":5,"n_constructed":0,"n_ran_checked":1,"n_instrument":4,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 4 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/crystal-structure-prediction-by-joint-1#ran","syntology_url":"https://syntology.ai/paper/2309.04475","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.04475"}},"official":{"repos":["jiaor17/DiffCSP"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/uncertainty-quantification-for-molecular","slug":"uncertainty-quantification-for-molecular","title":"Uncertainty Quantification for Molecular Property Predictions with Graph Neural Architecture Search","date":"2023-07-19","arxiv_id":"2307.10438","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/uncertainty-quantification-for-molecular#ran","syntology_url":"https://syntology.ai/paper/2307.10438","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.10438"}},"official":{"repos":["sjiang87/deephyper"],"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/pac-neural-prediction-set-learning-to","slug":"pac-neural-prediction-set-learning-to","title":"Selective Generation for Controllable Language Models","date":"2023-07-18","arxiv_id":"2307.09254","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":5,"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) · 2 unverified","sample_list":"/paper/pac-neural-prediction-set-learning-to#ran","syntology_url":"https://syntology.ai/paper/2307.09254","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.09254"}},"official":{"repos":["ml-postech/selective-generation"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/conformal-prediction-under-ambiguous-ground","slug":"conformal-prediction-under-ambiguous-ground","title":"Conformal prediction under ambiguous ground truth","date":"2023-07-18","arxiv_id":"2307.09302","repositories_listed":2,"syntology":{"n":19,"n_ran":15,"n_constructed":0,"n_ran_checked":10,"n_instrument":5,"n_unverified":4,"n_honours":1,"n_violates":0,"n_no_contract":9,"n_pointer_only":0,"phrase":"15 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 1 honoured, 0 violated, 9 with no contract checked; 5 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/conformal-prediction-under-ambiguous-ground#ran","syntology_url":"https://syntology.ai/paper/2307.09302","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.09302"}},"official":{"repos":["google-deepmind/uncertain_ground_truth"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/causality-oriented-robustness-exploiting","slug":"causality-oriented-robustness-exploiting","title":"Causality-oriented robustness: exploiting general noise interventions","date":"2023-07-18","arxiv_id":"2307.10299","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/causality-oriented-robustness-exploiting#ran","syntology_url":"https://syntology.ai/paper/2307.10299","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.10299"}},"official":{"repos":["xwshen51/drig"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/can-large-language-models-empower-molecular","slug":"can-large-language-models-empower-molecular","title":"Can Large Language Models Empower Molecular Property Prediction?","date":"2023-07-14","arxiv_id":"2307.07443","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/can-large-language-models-empower-molecular#ran","syntology_url":"https://syntology.ai/paper/2307.07443","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.07443"}},"official":{"repos":["chnq/llm4mol"],"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/scalable-deep-learning-for-rna-secondary","slug":"scalable-deep-learning-for-rna-secondary","title":"Scalable Deep Learning for RNA Secondary Structure Prediction","date":"2023-07-14","arxiv_id":"2307.10073","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 1 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/scalable-deep-learning-for-rna-secondary#ran","syntology_url":"https://syntology.ai/paper/2307.10073","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.10073"}},"official":{"repos":["automl/rnaformer"],"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/conformalization-of-sparse-generalized-linear","slug":"conformalization-of-sparse-generalized-linear","title":"Conformalization of Sparse Generalized Linear Models","date":"2023-07-11","arxiv_id":"2307.05109","repositories_listed":1,"syntology":{"n":4,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/conformalization-of-sparse-generalized-linear#ran","syntology_url":"https://syntology.ai/paper/2307.05109","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.05109"}},"official":{"repos":["etashguha/sparse_conformal"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/when-no-rejection-learning-is-optimal-for","slug":"when-no-rejection-learning-is-optimal-for","title":"When No-Rejection Learning is Consistent for Regression with Rejection","date":"2023-07-06","arxiv_id":"2307.02932","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":7,"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) · 1 unverified","sample_list":"/paper/when-no-rejection-learning-is-optimal-for#ran","syntology_url":"https://syntology.ai/paper/2307.02932","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.02932"}},"official":{"repos":["hanzhao-wang/rwr"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/assembled-openml-creating-efficient","slug":"assembled-openml-creating-efficient","title":"Assembled-OpenML: Creating Efficient Benchmarks for Ensembles in AutoML with OpenML","date":"2023-07-01","arxiv_id":"2307.00285","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/assembled-openml-creating-efficient#ran","syntology_url":"https://syntology.ai/paper/2307.00285","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.00285"}},"official":{"repos":["isg-siegen/assembled"],"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/dosediff-distance-aware-diffusion-model-for","slug":"dosediff-distance-aware-diffusion-model-for","title":"DoseDiff: Distance-aware Diffusion Model for Dose Prediction in Radiotherapy","date":"2023-06-28","arxiv_id":"2306.16324","repositories_listed":1,"syntology":{"n":13,"n_ran":9,"n_constructed":0,"n_ran_checked":5,"n_instrument":4,"n_unverified":4,"n_honours":3,"n_violates":0,"n_no_contract":2,"n_pointer_only":6,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 3 honoured, 0 violated, 2 with no contract checked; 4 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/dosediff-distance-aware-diffusion-model-for#ran","syntology_url":"https://syntology.ai/paper/2306.16324","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.16324"}},"official":{"repos":["whisney/dosediff"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/conformal-link-prediction-to-control-the","slug":"conformal-link-prediction-to-control-the","title":"Conformal link prediction for false discovery rate control","date":"2023-06-26","arxiv_id":"2306.14693","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/conformal-link-prediction-to-control-the#ran","syntology_url":"https://syntology.ai/paper/2306.14693","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.14693"}},"official":{"repos":["arianemarandon/linkpredconf"],"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/community-aware-transformer-for-autism","slug":"community-aware-transformer-for-autism","title":"Community-Aware Transformer for Autism Prediction in fMRI Connectome","date":"2023-06-24","arxiv_id":"2307.10181","repositories_listed":1,"syntology":{"n":11,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":11,"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) · 4 unverified","sample_list":"/paper/community-aware-transformer-for-autism#ran","syntology_url":"https://syntology.ai/paper/2307.10181","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.10181"}},"official":{"repos":["ubc-tea/com-braintf"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/how-to-efficiently-adapt-large-segmentation","slug":"how-to-efficiently-adapt-large-segmentation","title":"How to Efficiently Adapt Large Segmentation Model(SAM) to Medical Images","date":"2023-06-23","arxiv_id":"2306.13731","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/how-to-efficiently-adapt-large-segmentation#ran","syntology_url":"https://syntology.ai/paper/2306.13731","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.13731"}},"official":{"repos":["xhu248/autosam"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/road-barlow-twins-redundancy-reduction-for","slug":"road-barlow-twins-redundancy-reduction-for","title":"RedMotion: Motion Prediction via Redundancy Reduction","date":"2023-06-19","arxiv_id":"2306.10840","repositories_listed":3,"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/road-barlow-twins-redundancy-reduction-for#ran","syntology_url":"https://syntology.ai/paper/2306.10840","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.10840"}},"official":{"repos":["kit-mrt/red-motion","kit-mrt/road-barlow-twins","kit-mrt/future-motion"],"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/conformal-language-modeling","slug":"conformal-language-modeling","title":"Conformal Language Modeling","date":"2023-06-16","arxiv_id":"2306.10193","repositories_listed":2,"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/conformal-language-modeling#ran","syntology_url":"https://syntology.ai/paper/2306.10193","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.10193"}},"official":{"repos":["varal7/conformal-language-modeling"],"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/distribution-shift-inversion-for-out-of-1","slug":"distribution-shift-inversion-for-out-of-1","title":"Distribution Shift Inversion for Out-of-Distribution Prediction","date":"2023-06-14","arxiv_id":"2306.08328","repositories_listed":1,"syntology":{"n":16,"n_ran":8,"n_constructed":0,"n_ran_checked":7,"n_instrument":1,"n_unverified":8,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 8 unverified","sample_list":"/paper/distribution-shift-inversion-for-out-of-1#ran","syntology_url":"https://syntology.ai/paper/2306.08328","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.08328"}},"official":{"repos":["yu-rp/distribution-shift-iverson"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":8,"ran_from_kinds":["official"]}}},{"url":"/paper/automated-3d-pre-training-for-molecular","slug":"automated-3d-pre-training-for-molecular","title":"Automated 3D Pre-Training for Molecular Property Prediction","date":"2023-06-13","arxiv_id":"2306.07812","repositories_listed":1,"syntology":{"n":13,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":6,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":3,"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) · 6 unverified","sample_list":"/paper/automated-3d-pre-training-for-molecular#ran","syntology_url":"https://syntology.ai/paper/2306.07812","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.07812"}},"official":{"repos":["lars-research/3d-pgt"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/on-the-expected-size-of-conformal-prediction","slug":"on-the-expected-size-of-conformal-prediction","title":"On the Expected Size of Conformal Prediction Sets","date":"2023-06-12","arxiv_id":"2306.07254","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/on-the-expected-size-of-conformal-prediction#ran","syntology_url":"https://syntology.ai/paper/2306.07254","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.07254"}},"official":{"repos":["guneet-dhillon/expected-conformal-prediction-set-size"],"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/transformer-based-time-to-event-prediction","slug":"transformer-based-time-to-event-prediction","title":"Transformer-based Time-to-Event Prediction for Chronic Kidney Disease Deterioration","date":"2023-06-09","arxiv_id":"2306.05779","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":0,"n_instrument":4,"n_unverified":0,"n_honours":0,"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; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 4 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/transformer-based-time-to-event-prediction#ran","syntology_url":"https://syntology.ai/paper/2306.05779","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.05779"}},"official":{"repos":["dviraran/strafe"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/crysmmnet-multimodal-representation-for","slug":"crysmmnet-multimodal-representation-for","title":"CrysMMNet: Multimodal Representation for Crystal Property Prediction","date":"2023-06-09","arxiv_id":"2307.05390","repositories_listed":1,"syntology":{"n":7,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/crysmmnet-multimodal-representation-for#ran","syntology_url":"https://syntology.ai/paper/2307.05390","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.05390"}},"official":{"repos":["kdmsit/crysmmnet"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/genomic-interpreter-a-hierarchical-genomic","slug":"genomic-interpreter-a-hierarchical-genomic","title":"Genomic Interpreter: A Hierarchical Genomic Deep Neural Network with 1D Shifted Window Transformer","date":"2023-06-08","arxiv_id":"2306.05143","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":1,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/genomic-interpreter-a-hierarchical-genomic#ran","syntology_url":"https://syntology.ai/paper/2306.05143","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.05143"}},"official":{"repos":["zehui127/1d-swin"],"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/designing-decision-support-systems-using","slug":"designing-decision-support-systems-using","title":"Designing Decision Support Systems Using Counterfactual Prediction Sets","date":"2023-06-06","arxiv_id":"2306.03928","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/designing-decision-support-systems-using#ran","syntology_url":"https://syntology.ai/paper/2306.03928","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.03928"}},"official":{"repos":["networks-learning/counterfactual-prediction-sets"],"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/video-diffusion-models-with-local-global","slug":"video-diffusion-models-with-local-global","title":"Video Diffusion Models with Local-Global Context Guidance","date":"2023-06-05","arxiv_id":"2306.02562","repositories_listed":1,"syntology":{"n":17,"n_ran":16,"n_constructed":0,"n_ran_checked":16,"n_instrument":0,"n_unverified":1,"n_honours":2,"n_violates":3,"n_no_contract":11,"n_pointer_only":3,"phrase":"16 ran (of which 0 constructed an object rather than computing a result; 16 with no instrument failure: 2 honoured, 3 violated, 11 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/video-diffusion-models-with-local-global#ran","syntology_url":"https://syntology.ai/paper/2306.02562","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.02562"}},"official":{"repos":["exisas/lgc-vd"],"state":"official (archive's flag): 16 ran","n_ran":16,"n_constructed":0,"n_ran_no_instrument_failure":16,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/conformal-prediction-with-missing-values","slug":"conformal-prediction-with-missing-values","title":"Conformal Prediction with Missing Values","date":"2023-06-05","arxiv_id":"2306.02732","repositories_listed":1,"syntology":{"n":11,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/conformal-prediction-with-missing-values#ran","syntology_url":"https://syntology.ai/paper/2306.02732","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.02732"}},"official":{"repos":["mzaffran/conformalpredictionmissingvalues"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/probabilistic-concept-bottleneck-models","slug":"probabilistic-concept-bottleneck-models","title":"Probabilistic Concept Bottleneck Models","date":"2023-06-02","arxiv_id":"2306.01574","repositories_listed":2,"syntology":{"n":17,"n_ran":10,"n_constructed":4,"n_ran_checked":5,"n_instrument":5,"n_unverified":7,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"10 ran (of which 4 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 5 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/probabilistic-concept-bottleneck-models#ran","syntology_url":"https://syntology.ai/paper/2306.01574","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.01574"}},"official":{"repos":["ejkim47/prob-cbm"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":5,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/prediction-error-based-classification-for","slug":"prediction-error-based-classification-for","title":"Prediction Error-based Classification for Class-Incremental Learning","date":"2023-05-30","arxiv_id":"2305.18806","repositories_listed":1,"syntology":{"n":11,"n_ran":8,"n_constructed":5,"n_ran_checked":5,"n_instrument":3,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"8 ran (of which 5 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 3 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/prediction-error-based-classification-for#ran","syntology_url":"https://syntology.ai/paper/2305.18806","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.18806"}},"official":{"repos":["michalzajac-ml/pec"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":5,"n_ran_no_instrument_failure":5,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/conformal-prediction-with-large-language","slug":"conformal-prediction-with-large-language","title":"Conformal Prediction with Large Language Models for Multi-Choice Question Answering","date":"2023-05-28","arxiv_id":"2305.18404","repositories_listed":1,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/conformal-prediction-with-large-language#ran","syntology_url":"https://syntology.ai/paper/2305.18404","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.18404"}},"official":{"repos":["bhaweshiitk/conformalllm"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/explainable-brain-age-prediction-using","slug":"explainable-brain-age-prediction-using","title":"Explainable Brain Age Prediction using coVariance Neural Networks","date":"2023-05-27","arxiv_id":"2305.18370","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":1,"n_ran_checked":2,"n_instrument":1,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":4,"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) · 1 unverified","sample_list":"/paper/explainable-brain-age-prediction-using#ran","syntology_url":"https://syntology.ai/paper/2305.18370","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.18370"}},"official":{"repos":["sihags/vnn_brain_age"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":1,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/ovo-open-vocabulary-occupancy","slug":"ovo-open-vocabulary-occupancy","title":"OVO: Open-Vocabulary Occupancy","date":"2023-05-25","arxiv_id":"2305.16133","repositories_listed":1,"syntology":{"n":11,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":2,"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) · 2 unverified","sample_list":"/paper/ovo-open-vocabulary-occupancy#ran","syntology_url":"https://syntology.ai/paper/2305.16133","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.16133"}},"official":{"repos":["dzcgaara/OVO"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/speech-structured-prediction-with-energy","slug":"speech-structured-prediction-with-energy","title":"SPEECH: Structured Prediction with Energy-Based Event-Centric Hyperspheres","date":"2023-05-23","arxiv_id":"2305.13617","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":3,"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 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","sample_list":"/paper/speech-structured-prediction-with-energy#ran","syntology_url":"https://syntology.ai/paper/2305.13617","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.13617"}},"official":{"repos":["zjunlp/speech"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/video-prediction-models-as-rewards-for","slug":"video-prediction-models-as-rewards-for","title":"Video Prediction Models as Rewards for Reinforcement Learning","date":"2023-05-23","arxiv_id":"2305.14343","repositories_listed":3,"syntology":{"n":15,"n_ran":12,"n_constructed":0,"n_ran_checked":11,"n_instrument":1,"n_unverified":3,"n_honours":2,"n_violates":0,"n_no_contract":9,"n_pointer_only":1,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 2 honoured, 0 violated, 9 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/video-prediction-models-as-rewards-for#ran","syntology_url":"https://syntology.ai/paper/2305.14343","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.14343"}},"official":null}},{"url":"/paper/uncertainty-quantification-over-graph-with-1","slug":"uncertainty-quantification-over-graph-with-1","title":"Uncertainty Quantification over Graph with Conformalized Graph Neural Networks","date":"2023-05-23","arxiv_id":"2305.14535","repositories_listed":1,"syntology":{"n":6,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":6,"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) · 3 unverified","sample_list":"/paper/uncertainty-quantification-over-graph-with-1#ran","syntology_url":"https://syntology.ai/paper/2305.14535","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.14535"}},"official":{"repos":["snap-stanford/conformalized-gnn"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/learning-large-graph-property-prediction-via","slug":"learning-large-graph-property-prediction-via","title":"Learning Large Graph Property Prediction via Graph Segment Training","date":"2023-05-21","arxiv_id":"2305.12322","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":2,"n_no_contract":5,"n_pointer_only":4,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 2 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/learning-large-graph-property-prediction-via#ran","syntology_url":"https://syntology.ai/paper/2305.12322","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.12322"}},"official":{"repos":["kaidic/gst"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/anypredict-foundation-model-for-tabular","slug":"anypredict-foundation-model-for-tabular","title":"MediTab: Scaling Medical Tabular Data Predictors via Data Consolidation, Enrichment, and Refinement","date":"2023-05-20","arxiv_id":"2305.12081","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/anypredict-foundation-model-for-tabular#ran","syntology_url":"https://syntology.ai/paper/2305.12081","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.12081"}},"official":{"repos":["ryanwangzf/meditab"],"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/hahe-hierarchical-attention-for-hyper","slug":"hahe-hierarchical-attention-for-hyper","title":"HAHE: Hierarchical Attention for Hyper-Relational Knowledge Graphs in Global and Local Level","date":"2023-05-11","arxiv_id":"2305.06588","repositories_listed":1,"syntology":{"n":6,"n_ran":3,"n_constructed":3,"n_ran_checked":3,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","sample_list":"/paper/hahe-hierarchical-attention-for-hyper#ran","syntology_url":"https://syntology.ai/paper/2305.06588","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.06588"}},"official":{"repos":["lhrlab/hahe"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/masked-trajectory-models-for-prediction","slug":"masked-trajectory-models-for-prediction","title":"Masked Trajectory Models for Prediction, Representation, and Control","date":"2023-05-04","arxiv_id":"2305.02968","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/masked-trajectory-models-for-prediction#ran","syntology_url":"https://syntology.ai/paper/2305.02968","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.02968"}},"official":{"repos":["facebookresearch/mtm"],"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/towards-efficient-and-comprehensive-urban-1","slug":"towards-efficient-and-comprehensive-urban-1","title":"LibCity: A Unified Library Towards Efficient and Comprehensive Urban Spatial-Temporal Prediction","date":"2023-04-27","arxiv_id":"2304.14343","repositories_listed":2,"syntology":{"n":25,"n_ran":22,"n_constructed":0,"n_ran_checked":22,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":22,"n_pointer_only":2,"phrase":"22 ran (of which 0 constructed an object rather than computing a result; 22 with no instrument failure: 0 honoured, 0 violated, 22 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/towards-efficient-and-comprehensive-urban-1#ran","syntology_url":"https://syntology.ai/paper/2304.14343","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.14343"}},"official":{"repos":["libcity/bigscity-libcity-datasets","libcity/bigscity-libcity"],"state":"official (archive's flag): 22 ran","n_ran":22,"n_constructed":0,"n_ran_no_instrument_failure":22,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/generating-molecular-fragmentation-graphs","slug":"generating-molecular-fragmentation-graphs","title":"Generating Molecular Fragmentation Graphs with Autoregressive Neural Networks","date":"2023-04-25","arxiv_id":"2304.13136","repositories_listed":1,"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/generating-molecular-fragmentation-graphs#ran","syntology_url":"https://syntology.ai/paper/2304.13136","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.13136"}},"official":{"repos":["samgoldman97/ms-pred"],"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/eigenfold-generative-protein-structure","slug":"eigenfold-generative-protein-structure","title":"EigenFold: Generative Protein Structure Prediction with Diffusion Models","date":"2023-04-05","arxiv_id":"2304.02198","repositories_listed":1,"syntology":{"n":8,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/eigenfold-generative-protein-structure#ran","syntology_url":"https://syntology.ai/paper/2304.02198","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.02198"}},"official":{"repos":["bjing2016/eigenfold"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/conformal-prediction-regions-for-time-series","slug":"conformal-prediction-regions-for-time-series","title":"Conformal Prediction Regions for Time Series using Linear Complementarity Programming","date":"2023-04-03","arxiv_id":"2304.01075","repositories_listed":1,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":3,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/conformal-prediction-regions-for-time-series#ran","syntology_url":"https://syntology.ai/paper/2304.01075","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.01075"}},"official":{"repos":["earnedkibbles58/timeparamcpscores"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/dpf-learning-dense-prediction-fields-with","slug":"dpf-learning-dense-prediction-fields-with","title":"DPF: Learning Dense Prediction Fields with Weak Supervision","date":"2023-03-29","arxiv_id":"2303.16890","repositories_listed":1,"syntology":{"n":34,"n_ran":23,"n_constructed":13,"n_ran_checked":13,"n_instrument":10,"n_unverified":11,"n_honours":0,"n_violates":0,"n_no_contract":13,"n_pointer_only":34,"phrase":"23 ran (of which 13 constructed an object rather than computing a result; 13 with no instrument failure: 0 honoured, 0 violated, 13 with no contract checked; 10 where Syntology's instrument failed) · 11 unverified","sample_list":"/paper/dpf-learning-dense-prediction-fields-with#ran","syntology_url":"https://syntology.ai/paper/2303.16890","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.16890"}},"official":{"repos":["cxx226/dpf"],"state":"official (archive's flag): 22 ran","n_ran":22,"n_constructed":13,"n_ran_no_instrument_failure":13,"n_unverified":11,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/ensemble-based-blackbox-attacks-on-dense","slug":"ensemble-based-blackbox-attacks-on-dense","title":"Ensemble-based Blackbox Attacks on Dense Prediction","date":"2023-03-25","arxiv_id":"2303.14304","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/ensemble-based-blackbox-attacks-on-dense#ran","syntology_url":"https://syntology.ai/paper/2303.14304","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.14304"}},"official":{"repos":["csiplab/ebad"],"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/adaptive-conformal-prediction-by-reweighting","slug":"adaptive-conformal-prediction-by-reweighting","title":"Adaptive Conformal Prediction by Reweighting Nonconformity Score","date":"2023-03-22","arxiv_id":"2303.12695","repositories_listed":1,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/adaptive-conformal-prediction-by-reweighting#ran","syntology_url":"https://syntology.ai/paper/2303.12695","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.12695"}},"official":{"repos":["salimamoukou/acpi"],"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/magvlt-masked-generative-vision-and-language","slug":"magvlt-masked-generative-vision-and-language","title":"MAGVLT: Masked Generative Vision-and-Language Transformer","date":"2023-03-21","arxiv_id":"2303.12208","repositories_listed":1,"syntology":{"n":10,"n_ran":7,"n_constructed":5,"n_ran_checked":7,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 5 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) · 3 unverified","sample_list":"/paper/magvlt-masked-generative-vision-and-language#ran","syntology_url":"https://syntology.ai/paper/2303.12208","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.12208"}},"official":{"repos":["kakaobrain/magvlt"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":5,"n_ran_no_instrument_failure":7,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/imf-interactive-multimodal-fusion-model-for","slug":"imf-interactive-multimodal-fusion-model-for","title":"IMF: Interactive Multimodal Fusion Model for Link Prediction","date":"2023-03-20","arxiv_id":"2303.10816","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":3,"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/imf-interactive-multimodal-fusion-model-for#ran","syntology_url":"https://syntology.ai/paper/2303.10816","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.10816"}},"official":{"repos":["hestiasky/imf-pytorch"],"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/eqmotion-equivariant-multi-agent-motion","slug":"eqmotion-equivariant-multi-agent-motion","title":"EqMotion: Equivariant Multi-agent Motion Prediction with Invariant Interaction Reasoning","date":"2023-03-20","arxiv_id":"2303.10876","repositories_listed":2,"syntology":{"n":2,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":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) · 1 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/eqmotion-equivariant-multi-agent-motion#ran","syntology_url":"https://syntology.ai/paper/2303.10876","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.10876"}},"official":{"repos":["mediabrain-sjtu/eqmotion"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/leapfrog-diffusion-model-for-stochastic","slug":"leapfrog-diffusion-model-for-stochastic","title":"Leapfrog Diffusion Model for Stochastic Trajectory Prediction","date":"2023-03-20","arxiv_id":"2303.10895","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":1,"n_ran_checked":3,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":4,"phrase":"3 ran (of which 1 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/leapfrog-diffusion-model-for-stochastic#ran","syntology_url":"https://syntology.ai/paper/2303.10895","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.10895"}},"official":{"repos":["mediabrain-sjtu/led"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":1,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/improving-uncertainty-quantification-of-deep","slug":"improving-uncertainty-quantification-of-deep","title":"Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysis","date":"2023-03-19","arxiv_id":"2303.10694","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":1,"n_ran_checked":1,"n_instrument":4,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"5 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; 4 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/improving-uncertainty-quantification-of-deep#ran","syntology_url":"https://syntology.ai/paper/2303.10694","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.10694"}},"official":{"repos":["1995subhankar1995/ncp"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/surroundocc-multi-camera-3d-occupancy","slug":"surroundocc-multi-camera-3d-occupancy","title":"SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving","date":"2023-03-16","arxiv_id":"2303.09551","repositories_listed":2,"syntology":{"n":24,"n_ran":18,"n_constructed":0,"n_ran_checked":8,"n_instrument":10,"n_unverified":6,"n_honours":4,"n_violates":0,"n_no_contract":4,"n_pointer_only":21,"phrase":"18 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 4 honoured, 0 violated, 4 with no contract checked; 10 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/surroundocc-multi-camera-3d-occupancy#ran","syntology_url":"https://syntology.ai/paper/2303.09551","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.09551"}},"official":{"repos":["weiyithu/surroundocc"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/demystifying-causal-features-on-adversarial","slug":"demystifying-causal-features-on-adversarial","title":"Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network by Adversarial Instrumental Variable Regression","date":"2023-03-02","arxiv_id":"2303.01052","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/demystifying-causal-features-on-adversarial#ran","syntology_url":"https://syntology.ai/paper/2303.01052","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.01052"}},"official":{"repos":["ByungKwanLee/Causal-Adversarial-Instruments"],"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/single-cell-multimodal-prediction-via","slug":"single-cell-multimodal-prediction-via","title":"Single-Cell Multimodal Prediction via Transformers","date":"2023-03-01","arxiv_id":"2303.00233","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/single-cell-multimodal-prediction-via#ran","syntology_url":"https://syntology.ai/paper/2303.00233","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.00233"}},"official":{"repos":["omicsml/scmoformer"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/dirichlet-based-uncertainty-calibration-for","slug":"dirichlet-based-uncertainty-calibration-for","title":"Dirichlet-based Uncertainty Calibration for Active Domain Adaptation","date":"2023-02-27","arxiv_id":"2302.13824","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/dirichlet-based-uncertainty-calibration-for#ran","syntology_url":"https://syntology.ai/paper/2302.13824","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2302.13824"}},"official":{"repos":["bit-da/duc"],"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/knowledge-infused-contrastive-learning-for","slug":"knowledge-infused-contrastive-learning-for","title":"Knowledge-infused Contrastive Learning for Urban Imagery-based Socioeconomic Prediction","date":"2023-02-25","arxiv_id":"2302.13094","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/knowledge-infused-contrastive-learning-for#ran","syntology_url":"https://syntology.ai/paper/2302.13094","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2302.13094"}},"official":{"repos":["tsinghua-fib-lab/urbankg-knowcl"],"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/retrieved-sequence-augmentation-for-protein","slug":"retrieved-sequence-augmentation-for-protein","title":"Retrieved Sequence Augmentation for Protein Representation Learning","date":"2023-02-24","arxiv_id":"2302.12563","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/retrieved-sequence-augmentation-for-protein#ran","syntology_url":"https://syntology.ai/paper/2302.12563","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2302.12563"}},"official":{"repos":["hkunlp/rsa"],"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/improving-adaptive-conformal-prediction-using","slug":"improving-adaptive-conformal-prediction-using","title":"Improving Adaptive Conformal Prediction Using Self-Supervised Learning","date":"2023-02-23","arxiv_id":"2302.12238","repositories_listed":2,"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/improving-adaptive-conformal-prediction-using#ran","syntology_url":"https://syntology.ai/paper/2302.12238","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2302.12238"}},"official":{"repos":["seedatnabeel/sscp","vanderschaarlab/sscp"],"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/improved-online-conformal-prediction-via","slug":"improved-online-conformal-prediction-via","title":"Improved Online Conformal Prediction via Strongly Adaptive Online Learning","date":"2023-02-15","arxiv_id":"2302.07869","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/improved-online-conformal-prediction-via#ran","syntology_url":"https://syntology.ai/paper/2302.07869","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2302.07869"}},"official":{"repos":["salesforce/online_conformal"],"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"]}}}],"record_sha256":"7ad43a317f67a167ca1181760eb08629c9b32586a8200a1e0894499d59478b8d","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}