{"id":"https://openalex.org/W4412377217","doi":"https://doi.org/10.1145/3726302.3729957","title":"Parametric Retrieval Augmented Generation","display_name":"Parametric Retrieval Augmented Generation","publication_year":2025,"publication_date":"2025-07-13","ids":{"openalex":"https://openalex.org/W4412377217","doi":"https://doi.org/10.1145/3726302.3729957"},"language":"en","primary_location":{"id":"doi:10.1145/3726302.3729957","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729957","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729957","source":null,"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729957","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019662637","display_name":"Weihang Su","orcid":"https://orcid.org/0000-0002-8718-9402"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weihang Su","raw_affiliation_strings":["DCST, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"DCST, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103800447","display_name":"Y.C. Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yichen Tang","raw_affiliation_strings":["DCST, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"DCST, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089655391","display_name":"Qingyao Ai","orcid":"https://orcid.org/0000-0002-5030-709X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingyao Ai","raw_affiliation_strings":["DCST, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"DCST, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022903088","display_name":"Junxi Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junxi Yan","raw_affiliation_strings":["DCST, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"DCST, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104257043","display_name":"Changyue Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changyue Wang","raw_affiliation_strings":["DCST, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"DCST, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085094109","display_name":"Hongning Wang","orcid":"https://orcid.org/0000-0002-6524-9195"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongning Wang","raw_affiliation_strings":["DCST, Tsinghua University, Beijing, VA, USA"],"affiliations":[{"raw_affiliation_string":"DCST, Tsinghua University, Beijing, VA, USA","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017773628","display_name":"Ziyi Ye","orcid":"https://orcid.org/0000-0002-5622-0235"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyi Ye","raw_affiliation_strings":["DCST, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"DCST, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032133163","display_name":"Yujia Zhou","orcid":"https://orcid.org/0000-0002-3530-3787"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujia Zhou","raw_affiliation_strings":["DCST, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"DCST, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100668121","display_name":"Yiqun Liu","orcid":"https://orcid.org/0000-0002-0140-4512"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqun Liu","raw_affiliation_strings":["DCST, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"DCST, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5019662637"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":19.879,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.99155963,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1240","last_page":"1250"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9980999827384949,"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/T10028","display_name":"Topic Modeling","score":0.9980999827384949,"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":0.9961000084877014,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9927999973297119,"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/parametric-statistics","display_name":"Parametric statistics","score":0.6242973208427429},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6146199107170105},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1284741461277008},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10220813751220703}],"concepts":[{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6242973208427429},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6146199107170105},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1284741461277008},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10220813751220703}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3726302.3729957","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729957","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729957","source":null,"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3726302.3729957","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729957","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729957","source":null,"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412377217.pdf","grobid_xml":"https://content.openalex.org/works/W4412377217.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1982889956","https://openalex.org/W2964120615","https://openalex.org/W3027879771","https://openalex.org/W4252076394","https://openalex.org/W4385570777","https://openalex.org/W4385571865","https://openalex.org/W4387846439","https://openalex.org/W4391876619","https://openalex.org/W4400528650","https://openalex.org/W4400528754","https://openalex.org/W4401042753","https://openalex.org/W4404782967","https://openalex.org/W4404792852","https://openalex.org/W4405144021","https://openalex.org/W4409657405","https://openalex.org/W4412230188","https://openalex.org/W4412376859","https://openalex.org/W4412377063"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Retrieval-augmented":[0],"generation":[1],"(RAG)":[2],"has":[3,62],"emerged":[4],"as":[5,47,176],"a":[6,25,125],"promising":[7],"solution":[8],"to":[9,46,77,169,206],"enhance":[10],"the":[11,33,37,41,48,67,97,113,135,154,161,173,188,215,221],"reliability":[12],"of":[13,40,72,115,138,163,192],"large":[14],"language":[15],"models":[16,219],"(LLMs)":[17],"with":[18,202],"external":[19,131,164],"knowledge.":[20,179],"Existing":[21],"RAG":[22,127,185,204],"methods":[23,205],"share":[24],"common":[26],"strategy":[27],"for":[28],"knowledge":[29,50,92,105,132,165,193],"injection:":[30],"they":[31],"place":[32],"retrieved":[34],"documents":[35,74],"into":[36,134],"input":[38,98,155],"context":[39,68,156],"LLM,":[42],"which":[43],"we":[44,121],"refer":[45],"in-context":[49,91,116,203],"injection":[51,93],"method.":[52],"While":[53],"this":[54,119],"approach":[55,145],"is":[56],"simple":[57],"and":[58,70,81,190,218],"often":[59],"effective,":[60],"it":[61,171,198],"inherent":[63],"limitations.":[64],"Firstly,":[65],"increasing":[66],"length":[69],"number":[71],"relevant":[73],"can":[75,199],"lead":[76],"higher":[78],"computational":[79,150],"overhead":[80],"degraded":[82],"performance,":[83],"especially":[84],"in":[85,106,172,195,220],"complex":[86],"reasoning":[87],"tasks.":[88],"More":[89],"importantly,":[90],"operates":[94],"primarily":[95],"at":[96],"level,":[99],"but":[100,158],"LLMs":[101,168],"store":[102],"their":[103,107],"internal":[104,177],"parameters.":[108],"This":[109,144],"gap":[110],"fundamentally":[111],"limits":[112],"capacity":[114],"methods.":[117],"To":[118],"end,":[120],"introduce":[122],"Parametric":[123,184],"RAG,":[124],"new":[126],"paradigm":[128],"that":[129,183],"integrates":[130],"directly":[133],"feed-forward":[136],"networks":[137],"an":[139],"LLM":[140],"through":[141],"document":[142],"parameterization.":[143],"not":[146],"only":[147],"reduces":[148],"online":[149],"costs":[151],"by":[152,166],"shortening":[153],"length,":[157],"also":[159],"deepens":[160],"integration":[162],"enabling":[167],"utilize":[170],"same":[174],"way":[175],"parametric":[178],"Experimental":[180],"results":[181],"demonstrate":[182],"substantially":[186],"enhances":[187],"effectiveness":[189],"efficiency":[191],"augmentation":[194],"LLMs.":[196],"Also,":[197],"be":[200],"combined":[201],"achieve":[207],"even":[208],"better":[209],"performance.":[210],"We":[211],"have":[212],"open-sourced":[213],"all":[214],"code,":[216],"data,":[217],"following":[222],"GitHub":[223],"link:":[224],"https://github.com/oneal2000/PRAG":[225]},"counts_by_year":[{"year":2025,"cited_by_count":8}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}