{"id":"https://openalex.org/W7161684930","doi":"https://doi.org/10.48550/arxiv.2605.17159","title":"MADP: A Multi-Agent Pipeline for Sustainable Document Processing with Human-in-the-Loop","display_name":"MADP: A Multi-Agent Pipeline for Sustainable Document Processing with Human-in-the-Loop","publication_year":2026,"publication_date":"2026-05-16","ids":{"openalex":"https://openalex.org/W7161684930","doi":"https://doi.org/10.48550/arxiv.2605.17159"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.17159","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17159","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2605.17159","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136455720","display_name":"Diego Gosmar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gosmar, Diego","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5065189774","display_name":"Giovanni Zenezini","orcid":"https://orcid.org/0000-0002-0996-6739"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zenezini, Giovanni","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"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/T14347","display_name":"Big Data and Digital Economy","score":0.11940000206232071,"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"}},"topics":[{"id":"https://openalex.org/T14347","display_name":"Big Data and Digital Economy","score":0.11940000206232071,"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/T10028","display_name":"Topic Modeling","score":0.10980000346899033,"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/T13629","display_name":"Text Readability and Simplification","score":0.043299999088048935,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.7674999833106995},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7523000240325928},{"id":"https://openalex.org/keywords/automation","display_name":"Automation","score":0.7210000157356262},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.5421000123023987},{"id":"https://openalex.org/keywords/production","display_name":"Production (economics)","score":0.47429999709129333},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.46160000562667847},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.38989999890327454}],"concepts":[{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.7674999833106995},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7523000240325928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7497000098228455},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.7210000157356262},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.5421000123023987},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.47429999709129333},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.46160000562667847},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.45739999413490295},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.38989999890327454},{"id":"https://openalex.org/C67905146","wikidata":"https://www.wikidata.org/wiki/Q5287646","display_name":"Document processing","level":2,"score":0.36500000953674316},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.33469998836517334},{"id":"https://openalex.org/C2781089630","wikidata":"https://www.wikidata.org/wiki/Q21856745","display_name":"Realization (probability)","level":2,"score":0.3301999866962433},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31700000166893005},{"id":"https://openalex.org/C66204764","wikidata":"https://www.wikidata.org/wiki/Q219416","display_name":"Sustainability","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2904999852180481},{"id":"https://openalex.org/C98025372","wikidata":"https://www.wikidata.org/wiki/Q477538","display_name":"Systems architecture","level":3,"score":0.2775999903678894},{"id":"https://openalex.org/C21457203","wikidata":"https://www.wikidata.org/wiki/Q4056293","display_name":"Process automation system","level":3,"score":0.2759999930858612},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2752000093460083},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C63000827","wikidata":"https://www.wikidata.org/wiki/Q3080428","display_name":"Software portability","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2655999958515167},{"id":"https://openalex.org/C2780902518","wikidata":"https://www.wikidata.org/wiki/Q6033780","display_name":"Inheritance (genetic algorithm)","level":3,"score":0.26100000739097595}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.17159","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17159","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.17159","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17159","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":{"Document":[0],"processing":[1,31],"automation":[2,119],"remains":[3],"a":[4,21,65,70,84,94,116,130,158],"critical":[5],"challenge":[6,27],"in":[7,32,201],"enterprise":[8,33],"environments,":[9],"where":[10],"traditional":[11,184],"manual":[12,185],"approaches":[13],"are":[14],"labor-intensive":[15],"and":[16,40,63,69,177],"error-prone.":[17],"We":[18],"present":[19,157],"MADP,":[20],"multi-agent":[22],"architecture":[23],"that":[24,143,163],"addresses":[25],"the":[26,144],"of":[28,88,97,138,189],"automating":[29],"document":[30],"settings":[34],"by":[35,102,171,175,180],"combining":[36],"deep":[37],"learning-based":[38],"classification":[39],"parsing":[41],"with":[42,75,121,148],"large":[43],"language":[44],"model":[45],"extraction,":[46],"while":[47],"maintaining":[48],"accuracy":[49],"through":[50,112],"selective":[51],"human":[52],"validation.":[53],"Our":[54],"system":[55],"integrates":[56],"five":[57],"specialized":[58],"agents--Classificator,":[59],"Splitter,":[60],"Parser,":[61],"Extraction,":[62],"Validator--with":[64],"Human-in-the-Loop":[66,149],"(HITL)":[67],"mechanism":[68],"novel":[71],"Prompt":[72],"Fine":[73],"Tuning":[74],"Feedback":[76],"Inheritance":[77],"(PFTFI)":[78],"approach.":[79],"The":[80],"operational":[81],"analysis":[82,161],"on":[83,107,129],"production":[85,202],"use-case":[86],"scenario":[87],"100,000":[89],"invoices":[90],"per":[91,136],"year":[92],"indicates":[93],"potential":[95],"reduction":[96],"Full-Time":[98],"Equivalent":[99],"(FTE)":[100],"requirements":[101],"approximately":[103],"70%.":[104],"Production":[105],"deployment":[106,200],"955":[108],"real-world":[109],"documents":[110,135],"processed":[111],"January":[113],"2026":[114],"achieves":[115],"97.0%":[117],"full-pipeline":[118],"rate,":[120],"only":[122],"3%":[123],"requiring":[124],"non-AI":[125],"fallback.":[126],"Ablation":[127],"evaluation":[128],"stratified":[131],"100-document":[132],"subset":[133],"(5":[134],"each":[137],"20":[139],"supplier/document-type":[140],"categories)":[141],"demonstrates":[142],"full":[145],"MADP":[146],"configuration":[147],"supervision":[150],"attains":[151],"98.5%":[152],"document-level":[153],"accuracy.":[154],"Additionally,":[155],"we":[156],"comprehensive":[159],"sustainability":[160],"showing":[162],"our":[164],"hybrid":[165],"AI+HITL":[166],"approach":[167],"reduces":[168],"CO2":[169],"emissions":[170],"69%,":[172,176],"energy":[173],"consumption":[174],"water":[178],"usage":[179],"63%":[181],"compared":[182],"to":[183],"processing.":[186],"Benchmark":[187],"comparisons":[188],"multiple":[190],"LLM":[191],"backends":[192],"(Granite-Docling,":[193],"Mistral-Small,":[194],"DeepSeek-OCR)":[195],"provide":[196],"practical":[197],"insights":[198],"for":[199],"environments.":[203]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-20T00:00:00"}
