{"id":"https://openalex.org/W7162029884","doi":"https://doi.org/10.48550/arxiv.2605.20620","title":"Dynamic Shapley Computation","display_name":"Dynamic Shapley Computation","publication_year":2026,"publication_date":"2026-05-20","ids":{"openalex":"https://openalex.org/W7162029884","doi":"https://doi.org/10.48550/arxiv.2605.20620"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.20620","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20620","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.20620","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129800117","display_name":"Xuan Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Xuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074891591","display_name":"Hsi-Wen Chen","orcid":"https://orcid.org/0000-0002-7328-6367"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Hsi-Wen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136686726","display_name":"Ming-Syan Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Ming-Syan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136643907","display_name":"Jian Pei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pei, Jian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.31790000200271606,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.31790000200271606,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10991","display_name":"Game Theory and Voting Systems","score":0.1656000018119812,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.08669999986886978,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7278000116348267},{"id":"https://openalex.org/keywords/reuse","display_name":"Reuse","score":0.5982000231742859},{"id":"https://openalex.org/keywords/valuation","display_name":"Valuation (finance)","score":0.5867999792098999},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5336999893188477},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.49900001287460327},{"id":"https://openalex.org/keywords/shapley-value","display_name":"Shapley value","score":0.44670000672340393},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.41269999742507935}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7599999904632568},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7278000116348267},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.5982000231742859},{"id":"https://openalex.org/C186027771","wikidata":"https://www.wikidata.org/wiki/Q4008379","display_name":"Valuation (finance)","level":2,"score":0.5867999792098999},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5336999893188477},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.49900001287460327},{"id":"https://openalex.org/C199022921","wikidata":"https://www.wikidata.org/wiki/Q240046","display_name":"Shapley value","level":3,"score":0.44670000672340393},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.41269999742507935},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3594000041484833},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3483000099658966},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.34540000557899475},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2646999955177307},{"id":"https://openalex.org/C32407928","wikidata":"https://www.wikidata.org/wiki/Q2733833","display_name":"Best response","level":3,"score":0.260699987411499},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2574000060558319},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.20620","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20620","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.20620","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20620","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Shapley-based":[0],"data":[1],"valuation":[2,70,115,208],"provides":[3],"a":[4,37,56,64,72,86,113,124],"principled":[5],"way":[6],"to":[7,100,146,201],"quantify":[8],"the":[9,79,128,153,164,194],"contribution":[10],"of":[11,89,127,196,204],"training":[12,28,90,169],"data,":[13,170],"but":[14],"its":[15],"high":[16],"computational":[17],"cost":[18,195],"makes":[19],"it":[20],"impractical":[21],"in":[22,190],"dynamic":[23,69,114],"settings":[24],"where":[25],"tasks":[26,95],"and":[27,40,48,67,92,103,176,192],"players":[29,91,143],"evolve.":[30],"Existing":[31],"methods":[32],"treat":[33],"Shapley":[34,61],"computation":[35],"as":[36,63,71],"one-shot":[38],"process":[39],"collapse":[41],"contributions":[42],"into":[43],"aggregated":[44],"scores,":[45],"preventing":[46],"reuse":[47,175],"requiring":[49],"recomputation":[50],"under":[51],"any":[52],"change.":[53],"We":[54,77],"introduce":[55,160],"new":[57,130,142],"perspective":[58],"that":[59,81,93,117,185],"represents":[60],"values":[62],"player-by-task":[65],"matrix":[66,74,149,166],"formulates":[68],"structured":[73],"maintenance":[75],"problem.":[76],"exploit":[78],"fact":[80],"each":[82],"task":[83,131,188],"depends":[84],"on":[85,107],"small":[87,125],"subset":[88,174],"similar":[94,97],"yield":[96],"valuations,":[98],"leading":[99],"utility":[101],"locality":[102],"coalition":[104],"locality.":[105],"Based":[106],"these":[108],"insights,":[109],"we":[110,159],"propose":[111],"D-Shap,":[112],"framework":[116],"enables":[118],"efficient":[119],"updates":[120,139,189,198],"by":[121,141,172,199],"modifying":[122],"only":[123],"portion":[126],"matrix:":[129],"valuations":[132],"are":[133,144],"inferred":[134],"via":[135],"structure-aware":[136],"interpolation,":[137],"while":[138,206],"induced":[140],"confined":[145],"affected":[147],"local":[148],"blocks.":[150],"To":[151],"eliminate":[152],"need":[154],"for":[155],"pre-specified":[156],"evaluation":[157],"tasks,":[158],"self-valuation,":[161],"which":[162],"constructs":[163],"initial":[165],"directly":[167],"from":[168],"supported":[171],"scalable":[173],"coverage-aware":[177],"anchor":[178],"selection.":[179],"Experiments":[180],"across":[181],"diverse":[182],"models":[183],"show":[184],"D-Shap":[186],"performs":[187],"milliseconds":[191],"reduces":[193],"player":[197],"up":[200],"three":[202],"orders":[203],"magnitude,":[205],"achieving":[207],"quality":[209],"competitive":[210],"with":[211],"full":[212],"recomputation.":[213]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-22T00:00:00"}