{"id":"https://openalex.org/W7137906286","doi":"https://doi.org/10.48550/arxiv.2603.13933","title":"OmniCompliance-100K: A Multi-Domain, Rule-Grounded, Real-World Safety Compliance Dataset","display_name":"OmniCompliance-100K: A Multi-Domain, Rule-Grounded, Real-World Safety Compliance Dataset","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7137906286","doi":"https://doi.org/10.48550/arxiv.2603.13933"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.13933","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13933","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.13933","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129680134","display_name":"Wenbin Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Wenbin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5099230380","display_name":"Huihao Jing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jing, Huihao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066687788","display_name":"Haochen Shi","orcid":"https://orcid.org/0000-0002-9999-8979"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Haochen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129712049","display_name":"Changxuan Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Changxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129733460","display_name":"Haoran Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Haoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129727324","display_name":"Yangqiu Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Yangqiu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.1412999927997589,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.1412999927997589,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T14347","display_name":"Big Data and Digital Economy","score":0.08799999952316284,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.08659999817609787,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.7653999924659729},{"id":"https://openalex.org/keywords/compliance","display_name":"Compliance (psychology)","score":0.6136999726295471},{"id":"https://openalex.org/keywords/economic-shortage","display_name":"Economic shortage","score":0.5383999943733215},{"id":"https://openalex.org/keywords/risk-management","display_name":"Risk management","score":0.4438000023365021},{"id":"https://openalex.org/keywords/risk-assessment","display_name":"Risk assessment","score":0.3675000071525574},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.3528999984264374},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.34940001368522644}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.7653999924659729},{"id":"https://openalex.org/C2781460075","wikidata":"https://www.wikidata.org/wiki/Q1399332","display_name":"Compliance (psychology)","level":2,"score":0.6136999726295471},{"id":"https://openalex.org/C194051981","wikidata":"https://www.wikidata.org/wiki/Q1337691","display_name":"Economic shortage","level":3,"score":0.5383999943733215},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.5232999920845032},{"id":"https://openalex.org/C32896092","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Risk management","level":2,"score":0.4438000023365021},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.41659998893737793},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.4050999879837036},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3817000091075897},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.3675000071525574},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.3528999984264374},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.34940001368522644},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.3352999985218048},{"id":"https://openalex.org/C2779328685","wikidata":"https://www.wikidata.org/wiki/Q1475557","display_name":"Patient safety","level":3,"score":0.3330000042915344},{"id":"https://openalex.org/C2778306010","wikidata":"https://www.wikidata.org/wiki/Q606563","display_name":"Health Insurance Portability and Accountability Act","level":3,"score":0.329800009727478},{"id":"https://openalex.org/C2779240384","wikidata":"https://www.wikidata.org/wiki/Q1561274","display_name":"Safety culture","level":2,"score":0.31369999051094055},{"id":"https://openalex.org/C165609540","wikidata":"https://www.wikidata.org/wiki/Q1172486","display_name":"Data breach","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2818000018596649},{"id":"https://openalex.org/C184356942","wikidata":"https://www.wikidata.org/wiki/Q830382","display_name":"Best practice","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C2909164965","wikidata":"https://www.wikidata.org/wiki/Q6014597","display_name":"Incident report","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C187155963","wikidata":"https://www.wikidata.org/wiki/Q629029","display_name":"Occupational safety and health","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.13933","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13933","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.13933","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13933","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":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7814351320266724}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Ensuring":[0],"the":[1,151,165],"safety":[2,17,56,99,166,194],"and":[3,27,85,95,100,109,124,138,153,167],"compliance":[4,60,142,168],"of":[5,11,33,91,126,170],"large":[6],"language":[7],"models":[8],"(LLMs)":[9],"is":[10],"paramount":[12],"importance.":[13],"However,":[14],"existing":[15],"LLM":[16,193],"datasets":[18],"often":[19],"rely":[20],"on":[21],"ad-hoc":[22],"taxonomies":[23],"for":[24,40,191],"data":[25,102],"generation":[26],"suffer":[28],"from":[29,58,76,105],"a":[30,54,59,63,69,88,147],"significant":[31],"shortage":[32],"rule-grounded,":[34,70],"real-world":[35,71,141],"cases":[36],"that":[37,183],"are":[38],"essential":[39],"robustly":[41],"protecting":[42],"LLMs.":[43],"In":[44,130],"this":[45,49],"work,":[46],"we":[47,67],"address":[48],"critical":[50],"gap":[51],"by":[52],"constructing":[53],"comprehensive":[55],"dataset":[57,73,81,133],"perspective.":[61],"Using":[62],"powerful":[64],"web-searching":[65],"agent,":[66],"collect":[68],"case":[72],"OmniCompliance-100K,":[74],"sourced":[75],"multi-domain":[77],"authoritative":[78],"references.":[79],"The":[80],"spans":[82],"74":[83],"regulations":[84],"policies":[86,104],"across":[87,173],"wide":[89],"range":[90],"domains,":[92],"including":[93],"security":[94,114],"privacy":[96,103],"regulations,":[97],"content":[98],"user":[101],"leading":[106],"AI":[107],"companies":[108],"social":[110],"media":[111],"platforms,":[112],"financial":[113],"requirements,":[115],"medical":[116],"device":[117],"risk":[118],"management":[119],"standards,":[120],"educational":[121],"integrity":[122],"guidelines,":[123],"protections":[125],"fundamental":[127],"human":[128],"rights.":[129],"total,":[131],"our":[132],"contains":[134],"12,985":[135],"distinct":[136],"rules":[137,152],"106,009":[139],"associated":[140],"cases.":[143,156],"Our":[144,177],"analysis":[145],"confirms":[146],"strong":[148],"alignment":[149],"between":[150],"their":[154],"corresponding":[155],"We":[157],"further":[158],"conduct":[159],"extensive":[160],"benchmarking":[161],"experiments":[162,178],"to":[163,187],"evaluate":[164],"capabilities":[169],"advanced":[171],"LLMs":[172],"different":[174],"model":[175],"scales.":[176],"reveal":[179],"several":[180],"interesting":[181],"findings":[182],"have":[184],"great":[185],"potential":[186],"offer":[188],"valuable":[189],"insights":[190],"future":[192],"research.":[195]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-18T00:00:00"}