{"id":"https://openalex.org/W4416017480","doi":"https://doi.org/10.1145/3746252.3761136","title":"Reinforcement Learning-Driven Generative Retrieval with Semantic-aligned Multi-Layer Identifiers","display_name":"Reinforcement Learning-Driven Generative Retrieval with Semantic-aligned Multi-Layer Identifiers","publication_year":2025,"publication_date":"2025-11-08","ids":{"openalex":"https://openalex.org/W4416017480","doi":"https://doi.org/10.1145/3746252.3761136"},"language":null,"primary_location":{"id":"doi:10.1145/3746252.3761136","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761136","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5062895972","display_name":"Bo Xu","orcid":"https://orcid.org/0000-0001-5453-978X"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bo Xu","raw_affiliation_strings":["School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China"],"raw_orcid":"https://orcid.org/0000-0001-5453-978X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yicen Tian","orcid":"https://orcid.org/0009-0002-1953-4793"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yicen Tian","raw_affiliation_strings":["School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China"],"raw_orcid":"https://orcid.org/0009-0002-1953-4793","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100701286","display_name":"Xiaokun Zhang","orcid":"https://orcid.org/0000-0002-9755-2471"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiaokun Zhang","raw_affiliation_strings":["City University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0002-9755-2471","affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111270972","display_name":"Erchen Yu","orcid":"https://orcid.org/0009-0005-7489-1226"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Erchen Yu","raw_affiliation_strings":["School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China"],"raw_orcid":"https://orcid.org/0009-0005-7489-1226","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000533603","display_name":"Dailin Li","orcid":"https://orcid.org/0009-0003-5731-1790"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dailin Li","raw_affiliation_strings":["School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China"],"raw_orcid":"https://orcid.org/0009-0003-5731-1790","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030649664","display_name":"Linlin Zong","orcid":"https://orcid.org/0000-0002-1116-1016"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linlin Zong","raw_affiliation_strings":["School of Software, Dalian University of Technology, Dalian, Liaoning, China"],"raw_orcid":"https://orcid.org/0000-0002-1116-1016","affiliations":[{"raw_affiliation_string":"School of Software, Dalian University of Technology, Dalian, Liaoning, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023931221","display_name":"Hongfei Lin","orcid":"https://orcid.org/0000-0003-0872-7688"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongfei Lin","raw_affiliation_strings":["School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China"],"raw_orcid":"https://orcid.org/0000-0003-0872-7688","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5062895972"],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.45535611,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3592","last_page":"3601"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.7602999806404114,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.7602999806404114,"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":0.10930000245571136,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.017000000923871994,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.6647999882698059},{"id":"https://openalex.org/keywords/identifier","display_name":"Identifier","score":0.6448000073432922},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5580000281333923},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.531499981880188},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.48339998722076416},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.46219998598098755},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.43849998712539673},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.3871000111103058}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8163999915122986},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6647999882698059},{"id":"https://openalex.org/C154504017","wikidata":"https://www.wikidata.org/wiki/Q853614","display_name":"Identifier","level":2,"score":0.6448000073432922},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6021999716758728},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5580000281333923},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.531499981880188},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5184000134468079},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.48339998722076416},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.46219998598098755},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.43849998712539673},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.43050000071525574},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3871000111103058},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3797999918460846},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.36469998955726624},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3165000081062317},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.29179999232292175},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28790000081062317},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C2779597229","wikidata":"https://www.wikidata.org/wiki/Q17146505","display_name":"Similarity learning","level":3,"score":0.2718000113964081},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.2655999958515167},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.25529998540878296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746252.3761136","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761136","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2470818894","https://openalex.org/W2912924812","https://openalex.org/W2962985038","https://openalex.org/W3034999214","https://openalex.org/W3099700870","https://openalex.org/W4252076394","https://openalex.org/W4385571319","https://openalex.org/W4387848863","https://openalex.org/W4389519106","https://openalex.org/W4389520393","https://openalex.org/W4393153307","https://openalex.org/W4399301659","https://openalex.org/W4400525588","https://openalex.org/W4400531953","https://openalex.org/W4402670063","https://openalex.org/W4409365967"],"related_works":[],"abstract_inverted_index":{"Generative":[0],"retrieval":[1,3,31,42,101,142,155],"enhances":[2],"effectiveness":[4],"by":[5],"generating":[6],"natural":[7],"language":[8],"represented":[9],"document":[10,77],"identifiers.":[11,87,105,128],"However,":[12],"current":[13],"methods":[14],"often":[15],"struggle":[16],"with":[17,45],"two":[18],"major":[19],"challenges:":[20],"limited":[21,30],"identifier":[22,54],"quality":[23],"and":[24,49,72,118,152],"insufficient":[25],"query-document":[26,90],"interaction,":[27,91],"leading":[28],"to":[29,63,74,84,124],"performance.":[32],"To":[33,52,88],"tackle":[34],"these":[35,86],"challenges,":[36],"we":[37,56,80,92],"propose":[38],"a":[39,58,94,109,119,145],"novel":[40],"generative":[41,141],"framework":[43,137],"integrated":[44],"semantic-aligned":[46],"multi-layer":[47,104],"identifiers":[48],"reinforcement":[50,111],"learning.":[51],"improve":[53,89],"quality,":[55],"design":[57],"prompt-driven":[59],"multi-task":[60],"learning":[61,112],"strategy":[62,123],"generate":[64],"three":[65],"types":[66],"of":[67],"hierarchical":[68],"identifiers:":[69],"summary,":[70],"keyword,":[71],"pseudo-query,":[73],"capture":[75],"multi-granularity":[76],"semantics.":[78],"Furthermore,":[79],"adopt":[81],"supervised":[82],"fine-tuning":[83],"integrate":[85],"devise":[93],"multi-view":[95],"ranking":[96],"fusion":[97],"mechanism":[98],"that":[99,135],"combines":[100],"results":[102],"across":[103],"We":[106],"further":[107],"employ":[108],"GRPO-based":[110],"based":[113],"on":[114,130],"dense":[115],"similarity":[116],"rewards":[117],"difficulty-aware":[120],"negative":[121],"sampling":[122],"optimize":[125],"the":[126],"generated":[127],"Experiments":[129],"multiple":[131],"benchmark":[132],"datasets":[133],"show":[134],"our":[136,160],"significantly":[138],"outperforms":[139],"existing":[140],"methods,":[143],"offering":[144],"promising":[146],"solution":[147],"for":[148,159],"building":[149],"more":[150],"effective":[151],"semantically":[153],"aligned":[154],"systems.":[156],"The":[157],"code":[158],"model":[161],"is":[162],"publicly":[163],"available":[164],"at":[165],"https://github.com/yicentian02/GRAM-RL.":[166]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-11-08T00:00:00"}
