{"id":"https://openalex.org/W7162490798","doi":"https://doi.org/10.48550/arxiv.2605.26835","title":"Helicase: Uncertainty-Guided Supply Chain Knowledge Graph Construction with Autonomous Multi-Agent LLMs","display_name":"Helicase: Uncertainty-Guided Supply Chain Knowledge Graph Construction with Autonomous Multi-Agent LLMs","publication_year":2026,"publication_date":"2026-05-26","ids":{"openalex":"https://openalex.org/W7162490798","doi":"https://doi.org/10.48550/arxiv.2605.26835"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.26835","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26835","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.26835","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137091443","display_name":"Yunbo Long","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Long, Yunbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018846201","display_name":"Haolang Zhao","orcid":"https://orcid.org/0000-0002-1275-8199"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Haolang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137153132","display_name":"Ge Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Ge","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5116188205","display_name":"Alexandra Brintrup","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brintrup, Alexandra","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/T11273","display_name":"Advanced Graph Neural Networks","score":0.7864000201225281,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.7864000201225281,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.08340000361204147,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.01810000091791153,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6894000172615051},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.6863999962806702},{"id":"https://openalex.org/keywords/supply-chain","display_name":"Supply chain","score":0.6137999892234802},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.4487000107765198},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4413999915122986},{"id":"https://openalex.org/keywords/commonsense-reasoning","display_name":"Commonsense reasoning","score":0.3878999948501587},{"id":"https://openalex.org/keywords/inference-engine","display_name":"Inference engine","score":0.3644999861717224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.71670001745224},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6894000172615051},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.6863999962806702},{"id":"https://openalex.org/C108713360","wikidata":"https://www.wikidata.org/wiki/Q1824206","display_name":"Supply chain","level":2,"score":0.6137999892234802},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.4487000107765198},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4413999915122986},{"id":"https://openalex.org/C193221554","wikidata":"https://www.wikidata.org/wiki/Q5153664","display_name":"Commonsense reasoning","level":2,"score":0.3878999948501587},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38199999928474426},{"id":"https://openalex.org/C46743427","wikidata":"https://www.wikidata.org/wiki/Q1341685","display_name":"Inference engine","level":3,"score":0.3644999861717224},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3578999936580658},{"id":"https://openalex.org/C9616225","wikidata":"https://www.wikidata.org/wiki/Q3929429","display_name":"Semantic reasoner","level":2,"score":0.34769999980926514},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3330000042915344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31459999084472656},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.303600013256073},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2944999933242798},{"id":"https://openalex.org/C33762810","wikidata":"https://www.wikidata.org/wiki/Q461671","display_name":"Data integrity","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2632000148296356},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.25440001487731934},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.26835","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26835","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.26835","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26835","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":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"LLM-based":[0],"multi-agent":[1,123],"systems":[2],"have":[3,59],"been":[4],"widely":[5],"adopted":[6],"for":[7,126],"knowledge":[8,79,130,159],"retrieval":[9],"and":[10,19,75,110,146,153,175,182,221],"report":[11],"generation,":[12],"synthesizing":[13],"known":[14],"information":[15,25],"through":[16,71,149],"web":[17,46],"search":[18],"textual":[20],"reasoning.":[21],"However,":[22],"many":[23],"critical":[24],"tasks":[26],"in":[27,62,103],"supply":[28,128,157,206],"chains":[29],"are":[30,36],"not":[31,95],"simple":[32],"one-shot":[33],"queries:":[34],"they":[35],"structural":[37,180],"inference":[38,181,217],"problems":[39],"requiring":[40],"multi-hop":[41,216],"reasoning":[42,111,189],"across":[43,190],"complex,":[44],"fragmented":[45],"resources.":[47],"Questions":[48],"such":[49,87],"as":[50],"\\textit{``Which":[51],"Tesla":[52],"components":[53],"use":[54],"lithium":[55],"from":[56,82],"Australian":[57],"mines?''}":[58],"no":[60],"answer":[61],"any":[63],"single":[64],"document;":[65],"answers":[66,98],"must":[67,90],"be":[68,91],"computationally":[69],"synthesized":[70],"the":[72,172,191],"autonomous":[73,122,188],"construction":[74],"analysis":[76],"of":[77,204],"dynamic":[78],"graphs":[80,160],"assembled":[81],"fragmented,":[83],"heterogeneous":[84],"sources.":[85],"Moreover,":[86],"discovery":[88],"processes":[89],"uncertainty-aware:":[92],"decisions":[93],"depend":[94],"only":[96],"on":[97,100],"but":[99],"calibrated":[101,183],"confidence":[102,184],"their":[104],"reliability,":[105],"traceable":[106],"to":[107,215],"source":[108],"quality":[109],"consistency.":[112],"To":[113,186],"address":[114],"this":[115],"capability":[116],"gap,":[117],"we":[118,195],"propose":[119],"\\textit{Helicase},":[120],"an":[121],"LLM":[124],"system":[125],"uncertainty-guided":[127],"chain":[129,158,207],"graph":[131],"construction.":[132],"\\textit{Helicase}":[133],"decomposes":[134],"high-level":[135],"supply-chain":[136],"queries":[137,208],"into":[138,210],"executable":[139],"investigation":[140],"plans,":[141],"coordinates":[142],"specialized":[143],"web-search,":[144],"reasoning,":[145],"coding":[147],"agents":[148],"iterative":[150],"verification":[151],"loops,":[152],"incrementally":[154],"constructs":[155],"query-specific":[156],"with":[161],"per-fact":[162],"uncertainty":[163,167,170],"annotations.":[164],"Its":[165],"three-layer":[166],"framework":[168],"tracks":[169],"at":[171],"action,":[173],"trajectory,":[174],"memory":[176],"layers,":[177],"enabling":[178],"both":[179,219],"assessment.":[185],"evaluate":[187],"full":[192],"complexity":[193],"spectrum,":[194],"introduce":[196],"SCQA":[197],"(Supply":[198],"Chain":[199],"Query":[200],"Assessment),":[201],"a":[202],"benchmark":[203],"80":[205],"organized":[209],"four":[211],"quadrants":[212],"spanning":[213],"single-hop":[214],"under":[218],"high":[220],"low":[222],"data":[223],"visibility.":[224]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-28T00:00:00"}