{"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/data-valuation/papers/ran/1","list_of":"/task/data-valuation","task":"Data Valuation","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":1,"pages_in_order":1,"rows_per_page":100,"rows":[1,21],"of":21,"counts":{"archive_papers_tagged":119,"with_a_code_link":53,"where_syntology_ran_a_sample":21,"not_listed_spam_title":0,"listed":119,"listed_where_code_ran":21,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":17,"every_run_a_failure_of_syntologys_instrument":4,"listed_with_a_run_with_no_instrument_failure":17,"listed_every_run_a_failure_of_syntologys_instrument":4,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/data-valuation/papers/ran/1","prev":null,"next":null,"papers":[{"url":"/paper/faithful-group-shapley-value","slug":"faithful-group-shapley-value","title":"Faithful Group Shapley Value","date":"2025-05-25","arxiv_id":"2505.19013","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/faithful-group-shapley-value#ran","syntology_url":"https://syntology.ai/paper/2505.19013","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2505.19013"}},"official":{"repos":["kiljael/faithful_gsv"],"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/one-sample-fits-all-approximating-all","slug":"one-sample-fits-all-approximating-all","title":"One Sample Fits All: Approximating All Probabilistic Values Simultaneously and Efficiently","date":"2024-10-31","arxiv_id":"2410.23808","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":0,"n_no_contract":1,"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, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/one-sample-fits-all-approximating-all#ran","syntology_url":"https://syntology.ai/paper/2410.23808","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.23808"}},"official":{"repos":["watml/one-for-all"],"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/data-distribution-valuation","slug":"data-distribution-valuation","title":"Data Distribution Valuation","date":"2024-10-06","arxiv_id":"2410.04386","repositories_listed":1,"syntology":{"n":13,"n_ran":12,"n_constructed":0,"n_ran_checked":9,"n_instrument":3,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":8,"n_pointer_only":0,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 1 honoured, 0 violated, 8 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/data-distribution-valuation#ran","syntology_url":"https://syntology.ai/paper/2410.04386","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.04386"}},"official":{"repos":["xinyiys/data_distribution_valuation"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/shapiq-shapley-interactions-for-machine","slug":"shapiq-shapley-interactions-for-machine","title":"shapiq: Shapley Interactions for Machine Learning","date":"2024-10-02","arxiv_id":"2410.01649","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/shapiq-shapley-interactions-for-machine#ran","syntology_url":"https://syntology.ai/paper/2410.01649","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.01649"}},"official":{"repos":["mmschlk/shapiq"],"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/influence-based-attributions-can-be","slug":"influence-based-attributions-can-be","title":"Influence-based Attributions can be Manipulated","date":"2024-09-08","arxiv_id":"2409.05208","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":1,"n_instrument":3,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":5,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/influence-based-attributions-can-be#ran","syntology_url":"https://syntology.ai/paper/2409.05208","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2409.05208"}},"official":{"repos":["infinite-pursuits/influence-based-attributions-can-be-manipulated"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/chg-shapley-efficient-data-valuation-and","slug":"chg-shapley-efficient-data-valuation-and","title":"CHG Shapley: Efficient Data Valuation and Selection towards Trustworthy Machine Learning","date":"2024-06-17","arxiv_id":"2406.11730","repositories_listed":2,"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/chg-shapley-efficient-data-valuation-and#ran","syntology_url":"https://syntology.ai/paper/2406.11730","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.11730"}},"official":{"repos":["caihuaiguang/CHG-Shapley-for-Data-Selection","caihuaiguang/CHG-Shapley-for-Data-Valuation"],"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/redefining-contributions-shapley-driven","slug":"redefining-contributions-shapley-driven","title":"Redefining Contributions: Shapley-Driven Federated Learning","date":"2024-06-01","arxiv_id":"2406.00569","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":1,"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: 0 honoured, 1 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/redefining-contributions-shapley-driven#ran","syntology_url":"https://syntology.ai/paper/2406.00569","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.00569"}},"official":{"repos":["tnurbek/shapfed"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/scaling-laws-for-the-value-of-individual-data","slug":"scaling-laws-for-the-value-of-individual-data","title":"Scaling Laws for the Value of Individual Data Points in Machine Learning","date":"2024-05-30","arxiv_id":"2405.20456","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/scaling-laws-for-the-value-of-individual-data#ran","syntology_url":"https://syntology.ai/paper/2405.20456","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.20456"}},"official":{"repos":["iancovert/data-scaling"],"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/what-is-your-data-worth-to-gpt-llm-scale-data","slug":"what-is-your-data-worth-to-gpt-llm-scale-data","title":"What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions","date":"2024-05-22","arxiv_id":"2405.13954","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/what-is-your-data-worth-to-gpt-llm-scale-data#ran","syntology_url":"https://syntology.ai/paper/2405.13954","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.13954"}},"official":{"repos":["logix-project/logix"],"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/interpretable-machine-learning-for-tabpfn","slug":"interpretable-machine-learning-for-tabpfn","title":"Interpretable Machine Learning for TabPFN","date":"2024-03-16","arxiv_id":"2403.10923","repositories_listed":1,"syntology":{"n":12,"n_ran":12,"n_constructed":0,"n_ran_checked":12,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":12,"n_pointer_only":1,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/interpretable-machine-learning-for-tabpfn#ran","syntology_url":"https://syntology.ai/paper/2403.10923","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.10923"}},"official":{"repos":["david-rundel/tabpfn_iml"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":12,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/stochastic-amortization-a-unified-approach-to","slug":"stochastic-amortization-a-unified-approach-to","title":"Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution","date":"2024-01-29","arxiv_id":"2401.15866","repositories_listed":3,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/stochastic-amortization-a-unified-approach-to#ran","syntology_url":"https://syntology.ai/paper/2401.15866","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.15866"}},"official":{"repos":["chanwkimlab/amortized-attribution","chanwkimlab/xai-amortization","iancovert/amortized-valuation"],"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/opendataval-a-unified-benchmark-for-data-1","slug":"opendataval-a-unified-benchmark-for-data-1","title":"OpenDataVal: a Unified Benchmark for Data Valuation","date":"2023-06-18","arxiv_id":"2306.10577","repositories_listed":2,"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/opendataval-a-unified-benchmark-for-data-1#ran","syntology_url":"https://syntology.ai/paper/2306.10577","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.10577"}},"official":{"repos":["opendataval/opendataval"],"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/data-valuation-the-partial-ordinal-shapley","slug":"data-valuation-the-partial-ordinal-shapley","title":"Data valuation: The partial ordinal Shapley value for machine learning","date":"2023-05-02","arxiv_id":"2305.01660","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/data-valuation-the-partial-ordinal-shapley#ran","syntology_url":"https://syntology.ai/paper/2305.01660","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.01660"}},"official":{"repos":["peizhengwang/partialordinalshapley"],"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/lava-data-valuation-without-pre-specified","slug":"lava-data-valuation-without-pre-specified","title":"LAVA: Data Valuation without Pre-Specified Learning Algorithms","date":"2023-04-28","arxiv_id":"2305.00054","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/lava-data-valuation-without-pre-specified#ran","syntology_url":"https://syntology.ai/paper/2305.00054","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.00054"}},"official":{"repos":["ruoxi-jia-group/lava"],"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/fairshap-a-data-re-weighting-approach-for","slug":"fairshap-a-data-re-weighting-approach-for","title":"Towards Algorithmic Fairness by means of Instance-level Data Re-weighting based on Shapley Values","date":"2023-03-03","arxiv_id":"2303.01928","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/fairshap-a-data-re-weighting-approach-for#ran","syntology_url":"https://syntology.ai/paper/2303.01928","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.01928"}},"official":{"repos":["AdrianArnaiz/fair-shap"],"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/probably-approximate-shapley-fairness-with","slug":"probably-approximate-shapley-fairness-with","title":"Probably Approximate Shapley Fairness with Applications in Machine Learning","date":"2022-12-01","arxiv_id":"2212.00630","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/probably-approximate-shapley-fairness-with#ran","syntology_url":"https://syntology.ai/paper/2212.00630","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2212.00630"}},"official":{"repos":["BobbyZhouZijian/ProbablyApproximateShapleyFairness"],"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/the-shapley-value-in-machine-learning","slug":"the-shapley-value-in-machine-learning","title":"The Shapley Value in Machine Learning","date":"2022-02-11","arxiv_id":"2202.05594","repositories_listed":3,"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/the-shapley-value-in-machine-learning#ran","syntology_url":"https://syntology.ai/paper/2202.05594","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.05594"}},"official":{"repos":["benedekrozemberczki/shapley"],"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/incentivizing-collaboration-in-machine","slug":"incentivizing-collaboration-in-machine","title":"Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards","date":"2021-12-17","arxiv_id":"2112.09327","repositories_listed":1,"syntology":{"n":18,"n_ran":16,"n_constructed":0,"n_ran_checked":16,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":16,"n_pointer_only":0,"phrase":"16 ran (of which 0 constructed an object rather than computing a result; 16 with no instrument failure: 0 honoured, 0 violated, 16 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/incentivizing-collaboration-in-machine#ran","syntology_url":"https://syntology.ai/paper/2112.09327","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.09327"}},"official":{"repos":["XinyiYS/CML-RewardDistribution"],"state":"official (archive's flag): 16 ran","n_ran":16,"n_constructed":0,"n_ran_no_instrument_failure":16,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/data-valuation-using-reinforcement-learning","slug":"data-valuation-using-reinforcement-learning","title":"Data Valuation using Reinforcement Learning","date":"2019-09-25","arxiv_id":"1909.11671","repositories_listed":2,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/data-valuation-using-reinforcement-learning#ran","syntology_url":"https://syntology.ai/paper/1909.11671","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.11671"}},"official":{"repos":["google-research/google-research"],"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/efficient-task-specific-data-valuation-for","slug":"efficient-task-specific-data-valuation-for","title":"Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms","date":"2019-08-22","arxiv_id":"1908.08619","repositories_listed":3,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":2,"n_honours":1,"n_violates":2,"n_no_contract":0,"n_pointer_only":5,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 2 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/efficient-task-specific-data-valuation-for#ran","syntology_url":"https://syntology.ai/paper/1908.08619","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.08619"}},"official":{"repos":["AI-secure/KNN-PVLDB"],"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/data-shapley-equitable-valuation-of-data-for","slug":"data-shapley-equitable-valuation-of-data-for","title":"Data Shapley: Equitable Valuation of Data for Machine Learning","date":"2019-04-05","arxiv_id":"1904.02868","repositories_listed":6,"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/data-shapley-equitable-valuation-of-data-for#ran","syntology_url":"https://syntology.ai/paper/1904.02868","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.02868"}},"official":{"repos":["amiratag/DataShapley"],"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"]}}}],"record_sha256":"56b564b15e87a5c4e1b276428617e8ed531dc6bee6c320b03e73b615e623a477","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}