{"id":"https://openalex.org/W7151562669","doi":"https://doi.org/10.1109/icmla66185.2025.00011","title":"Progressive Searching for Retrieval in RAG","display_name":"Progressive Searching for Retrieval in RAG","publication_year":2025,"publication_date":"2025-12-03","ids":{"openalex":"https://openalex.org/W7151562669","doi":"https://doi.org/10.1109/icmla66185.2025.00011"},"language":null,"primary_location":{"id":"doi:10.1109/icmla66185.2025.00011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla66185.2025.00011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Machine Learning and Applications (ICMLA)","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/A5072759053","display_name":"Taehee Jeong","orcid":null},"institutions":[{"id":"https://openalex.org/I51504820","display_name":"San Jose State University","ror":"https://ror.org/04qyvz380","country_code":"US","type":"education","lineage":["https://openalex.org/I51504820"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Taehee Jeong","raw_affiliation_strings":["San Jose State University"],"affiliations":[{"raw_affiliation_string":"San Jose State University","institution_ids":["https://openalex.org/I51504820"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125575732","display_name":"Xingzhe Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I51504820","display_name":"San Jose State University","ror":"https://ror.org/04qyvz380","country_code":"US","type":"education","lineage":["https://openalex.org/I51504820"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xingzhe Zhao","raw_affiliation_strings":["San Jose State University"],"affiliations":[{"raw_affiliation_string":"San Jose State University","institution_ids":["https://openalex.org/I51504820"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022437808","display_name":"P. Li","orcid":null},"institutions":[{"id":"https://openalex.org/I51504820","display_name":"San Jose State University","ror":"https://ror.org/04qyvz380","country_code":"US","type":"education","lineage":["https://openalex.org/I51504820"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peizu Li","raw_affiliation_strings":["San Jose State University"],"affiliations":[{"raw_affiliation_string":"San Jose State University","institution_ids":["https://openalex.org/I51504820"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133064204","display_name":"Markus Valvur","orcid":null},"institutions":[{"id":"https://openalex.org/I51504820","display_name":"San Jose State University","ror":"https://ror.org/04qyvz380","country_code":"US","type":"education","lineage":["https://openalex.org/I51504820"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Markus Valvur","raw_affiliation_strings":["San Jose State University"],"affiliations":[{"raw_affiliation_string":"San Jose State University","institution_ids":["https://openalex.org/I51504820"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112119138","display_name":"Weihua Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I51504820","display_name":"San Jose State University","ror":"https://ror.org/04qyvz380","country_code":"US","type":"education","lineage":["https://openalex.org/I51504820"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weihua Zhao","raw_affiliation_strings":["San Jose State University"],"affiliations":[{"raw_affiliation_string":"San Jose State University","institution_ids":["https://openalex.org/I51504820"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5072759053"],"corresponding_institution_ids":["https://openalex.org/I51504820"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.87688954,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"33","last_page":"38"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.2531000077724457,"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":0.2531000077724457,"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.05310000106692314,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.0471000000834465,"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/scalability","display_name":"Scalability","score":0.6446999907493591},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6044999957084656},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5724999904632568},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.527899980545044},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.5024999976158142},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4684999883174896},{"id":"https://openalex.org/keywords/data-retrieval","display_name":"Data retrieval","score":0.42910000681877136},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.39340001344680786}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7470999956130981},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6446999907493591},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6044999957084656},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5724999904632568},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.527899980545044},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.5024999976158142},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4684999883174896},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4666999876499176},{"id":"https://openalex.org/C551230270","wikidata":"https://www.wikidata.org/wiki/Q4368942","display_name":"Data retrieval","level":2,"score":0.42910000681877136},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.39340001344680786},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.3587000072002411},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3546000123023987},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34299999475479126},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C116425068","wikidata":"https://www.wikidata.org/wiki/Q4686695","display_name":"Adversarial information retrieval","level":5,"score":0.3140999972820282},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmla66185.2025.00011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla66185.2025.00011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Machine Learning and Applications (ICMLA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2122111042","https://openalex.org/W2124509324","https://openalex.org/W2963265099","https://openalex.org/W2963469388","https://openalex.org/W2972428398","https://openalex.org/W4401857375"],"related_works":[],"abstract_inverted_index":{"Retrieval-Augmented":[0],"Generation":[1],"(RAG)":[2],"is":[3,35,61,141],"a":[4,29,32,55,71,88,99,123],"promising":[5],"technique":[6],"for":[7,63,75,136],"mitigating":[8],"two":[9],"key":[10],"limitations":[11],"of":[12,90],"large":[13,137],"language":[14],"models":[15],"(LLMs):":[16],"outdated":[17],"information":[18],"and":[19,58,96,128,132],"hallucinations.":[20],"RAG":[21,64,120],"system":[22],"stores":[23],"documents":[24,47],"as":[25],"embedding":[26],"vectors":[27],"in":[28,119],"database.":[30],"Given":[31],"query,":[33],"search":[34,118],"executed":[36],"to":[37,53,65],"find":[38],"the":[39,44,84,110],"most":[40],"related":[41],"documents.":[42],"Then,":[43],"topmost":[45],"matching":[46],"are":[48],"inserted":[49],"into":[50,98],"LLMs\u2019":[51],"prompt":[52],"generate":[54],"response.":[56],"Efficient":[57],"accurate":[59],"searching":[60,73,80],"critical":[62],"get":[66],"relevant":[67],"information.":[68],"We":[69],"propose":[70],"cost-effective":[72],"algorithm":[74,81],"retrieval":[76,106,134],"process.":[77],"Our":[78,113,139],"progressive":[79,117],"incrementally":[82],"refines":[83],"candidate":[85],"set":[86],"through":[87],"hierarchy":[89],"searches,":[91],"starting":[92],"from":[93],"low-dimensional":[94],"embeddings":[95],"progressing":[97],"higher,":[100],"target-dimensionality.":[101],"This":[102],"multi-stage":[103],"approach":[104],"reduces":[105],"time":[107],"while":[108],"preserving":[109],"desired":[111],"accuracy.":[112],"findings":[114],"demonstrate":[115],"that":[116],"systems":[121],"achieves":[122],"balance":[124],"between":[125],"dimensionality,":[126],"speed,":[127],"accuracy,":[129],"enabling":[130],"scalable":[131],"high-performance":[133],"even":[135],"databases.":[138],"code":[140],"available":[142],"at":[143],"https://github.com/taeheej/Progressive-searching-for-Retrieval-in-RAG.":[144]},"counts_by_year":[],"updated_date":"2026-04-09T06:08:40.794217","created_date":"2026-04-08T00:00:00"}
