{"id":"https://openalex.org/W4415707367","doi":"https://doi.org/10.1109/tcyb.2025.3624234","title":"Enhancing Large Language Models for Fashion Smart Manufacturing via Dynamic Collaborative Routing-Based Retrieval Reranking","display_name":"Enhancing Large Language Models for Fashion Smart Manufacturing via Dynamic Collaborative Routing-Based Retrieval Reranking","publication_year":2025,"publication_date":"2025-10-30","ids":{"openalex":"https://openalex.org/W4415707367","doi":"https://doi.org/10.1109/tcyb.2025.3624234","pmid":"https://pubmed.ncbi.nlm.nih.gov/41166623"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2025.3624234","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2025.3624234","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103006369","display_name":"Kexin Sun","orcid":"https://orcid.org/0000-0001-5277-0304"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Kexin Sun","raw_affiliation_strings":["Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0001-5277-0304","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103467349","display_name":"Yujie Han","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yujie Han","raw_affiliation_strings":["Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081499025","display_name":"Zhiheng Zhao","orcid":"https://orcid.org/0000-0002-0024-8116"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhiheng Zhao","raw_affiliation_strings":["Department of Industrial and Systems Engineering and the Research Institute for Advanced Manufacturing, The Hong Kong Polytechnic University, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0002-0024-8116","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering and the Research Institute for Advanced Manufacturing, The Hong Kong Polytechnic University, Hong Kong, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101758679","display_name":"George Q. Huang","orcid":"https://orcid.org/0000-0003-3592-7917"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"George Q. Huang","raw_affiliation_strings":["Department of Industrial and Systems Engineering and the Research Institute for Advanced Manufacturing, The Hong Kong Polytechnic University, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0003-3592-7917","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering and the Research Institute for Advanced Manufacturing, The Hong Kong Polytechnic University, Hong Kong, China","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I14243506"],"apc_list":null,"apc_paid":null,"fwci":2.5399,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91152017,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"56","issue":"3","first_page":"1282","last_page":"1295"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.3727000057697296,"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":0.3727000057697296,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.05779999867081642,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.05590000003576279,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/boosting","display_name":"Boosting (machine learning)","score":0.48890000581741333},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.4749000072479248},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4413999915122986},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.43299999833106995},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4174000024795532},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3824999928474426},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.3513999879360199},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.33629998564720154}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8282999992370605},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5044999718666077},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.48890000581741333},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.4749000072479248},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4413999915122986},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.43299999833106995},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4174000024795532},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3982999920845032},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3824999928474426},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.3513999879360199},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.33629998564720154},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3334999978542328},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C85407183","wikidata":"https://www.wikidata.org/wiki/Q1045785","display_name":"Semantic network","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2913999855518341},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28610000014305115},{"id":"https://openalex.org/C175700187","wikidata":"https://www.wikidata.org/wiki/Q187939","display_name":"Manufacturing","level":2,"score":0.2784999907016754},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2768999934196472},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.2754000127315521},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.2732999920845032},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tcyb.2025.3624234","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2025.3624234","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cybernetics","raw_type":"journal-article"},{"id":"pmid:41166623","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41166623","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on cybernetics","raw_type":null},{"id":"pmh:oai:ira.lib.polyu.edu.hk:10397/117733","is_oa":false,"landing_page_url":"http://hdl.handle.net/10397/117733","pdf_url":null,"source":{"id":"https://openalex.org/S4306400205","display_name":"PolyU Institutional Research Archive (Hong Kong Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I14243506","host_organization_name":"Hong Kong Polytechnic University","host_organization_lineage":["https://openalex.org/I14243506"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal/Magazine Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G371722455","display_name":null,"funder_award_id":"C7076-22GF","funder_id":"https://openalex.org/F4320314062","funder_display_name":"National Research Council"},{"id":"https://openalex.org/G4714890029","display_name":null,"funder_award_id":"2024A1515011930","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G5385363192","display_name":null,"funder_award_id":"T32-707/22-N","funder_id":"https://openalex.org/F4320314062","funder_display_name":"National Research Council"},{"id":"https://openalex.org/G5953415293","display_name":null,"funder_award_id":"15203025","funder_id":"https://openalex.org/F4320314062","funder_display_name":"National Research Council"},{"id":"https://openalex.org/G8819798200","display_name":null,"funder_award_id":"52305557","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320314062","display_name":"National Research Council","ror":"https://ror.org/02eq2w707"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Enhancing":[0],"large":[1,58],"language":[2],"models":[3,99],"(LLMs)":[4],"with":[5,93,163],"external":[6],"knowledge":[7,226],"base":[8],"retrieval":[9,83],"in":[10,128,222],"the":[11,34,69,113,158,164,172,210,215,223],"fashion":[12,37,204,224],"manufacturing":[13,38,205,225],"industry":[14],"can":[15],"provide":[16],"more":[17],"reliable":[18],"technical":[19,45],"support":[20],"and":[21,28,47,63,72,120,148,171,180,183,187,201,212],"decision-making":[22],"assistance,":[23],"significantly":[24],"improving":[25],"process":[26,206],"control":[27],"boosting":[29],"intelligent":[30],"production":[31],"efficiency.":[32],"However,":[33],"field":[35],"of":[36,60,116,214],"involves":[39],"highly":[40],"specialized":[41],"terminology,":[42],"logically":[43],"complex":[44,135],"knowledge,":[46],"intricate":[48],"query":[49,165],"tasks.":[50],"Existing":[51],"simple":[52],"query-matching":[53],"techniques":[54],"often":[55],"return":[56],"a":[57,82,88,108,123,129,202],"number":[59],"contextually":[61,188],"loose":[62],"redundant":[64,152],"document":[65,140,190],"chunks,":[66],"severely":[67],"impacting":[68],"model's":[70],"understanding":[71],"response":[73],"quality.":[74],"To":[75],"address":[76],"this":[77,79],"issue,":[78],"article":[80],"proposes":[81],"optimization":[84],"framework":[85,114],"based":[86,154],"on":[87,155,194],"dynamic":[89],"capsule":[90,124],"routing":[91,125],"network":[92],"embedded":[94,127],"semantic":[95,100,130,168],"graph":[96,132],"(SGDCR),":[97],"which":[98],"relations":[101],"among":[102,138],"multiple":[103,146],"retrieved":[104],"documents":[105,153,160,173],"by":[106,176],"simulating":[107],"team":[109],"collaboration":[110],"mechanism.":[111],"Specifically,":[112],"consists":[115],"two":[117],"steps:":[118],"filtering":[119],"reranking.":[121],"First,":[122],"mechanism":[126],"association":[131],"dynamically":[133],"captures":[134],"contextual":[136],"relationships":[137],"coarse-grained":[139],"blocks,":[141],"learns":[142],"contribution":[143,181],"scores":[144,179,182],"for":[145],"documents,":[147],"filters":[149],"irrelevant":[150],"or":[151],"ranking.":[156],"Subsequently,":[157],"filtered":[159],"are":[161,174],"matched":[162],"through":[166],"deep":[167],"similarity":[169],"measurement,":[170],"reranked":[175],"integrating":[177],"relevance":[178],"generating":[184],"efficient,":[185],"accurate,":[186],"coherent":[189],"prompts.":[191],"Experimental":[192],"results":[193],"publicly":[195],"available":[196],"dense":[197],"open-domain":[198],"QA":[199,207,227],"datasets":[200],"constructed":[203],"dataset":[208],"demonstrate":[209],"effectiveness":[211],"superiority":[213],"proposed":[216],"method":[217],"over":[218],"existing":[219],"reranking":[220],"approaches":[221],"system.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-30T00:00:00"}