{"id":"https://openalex.org/W4416078617","doi":"https://doi.org/10.1145/3746252.3760855","title":"Exploring Reasoning-Infused Text Embedding with Large Language Models for Zero-Shot Dense Retrieval","display_name":"Exploring Reasoning-Infused Text Embedding with Large Language Models for Zero-Shot Dense Retrieval","publication_year":2025,"publication_date":"2025-11-10","ids":{"openalex":"https://openalex.org/W4416078617","doi":"https://doi.org/10.1145/3746252.3760855"},"language":null,"primary_location":{"id":"doi:10.1145/3746252.3760855","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746252.3760855","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3746252.3760855","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3746252.3760855","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001653256","display_name":"Yuxiang Liu","orcid":"https://orcid.org/0009-0004-2015-4848"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yuxiang Liu","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Urbana, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Urbana, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101289577","display_name":"Tian Wang","orcid":"https://orcid.org/0009-0008-7451-6153"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tian Wang","raw_affiliation_strings":["Amazon, Palo Alto, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Palo Alto, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045890591","display_name":"Gautam Kundu","orcid":"https://orcid.org/0009-0009-0872-3557"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gourab Kundu","raw_affiliation_strings":["Amazon, New York, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, New York, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115588849","display_name":"Tru H. Cao","orcid":"https://orcid.org/0009-0000-2960-6717"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianyu Cao","raw_affiliation_strings":["Amazon, Palo Alto, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Palo Alto, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101688179","display_name":"Guang Cheng","orcid":"https://orcid.org/0000-0002-7874-9404"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guang Cheng","raw_affiliation_strings":["Amazon, Los Angeles, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Los Angeles, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100297487","display_name":"Zhen Ge","orcid":"https://orcid.org/0009-0001-1525-8579"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhen Ge","raw_affiliation_strings":["Amazon, New York, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, New York, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088339142","display_name":"Jianshu Chen","orcid":"https://orcid.org/0000-0001-8216-2756"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianshu Chen","raw_affiliation_strings":["Amazon, Palo Alto, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Palo Alto, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068272021","display_name":"Qingjun Cui","orcid":"https://orcid.org/0000-0002-6600-9804"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qingjun Cui","raw_affiliation_strings":["Amazon, Palo Alto, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Palo Alto, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013670321","display_name":"Trishul Chilimbi","orcid":"https://orcid.org/0000-0001-6711-1117"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Trishul Chilimbi","raw_affiliation_strings":["Amazon, Palo Alto, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Palo Alto, USA","institution_ids":["https://openalex.org/I1311688040"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5001653256"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18761582,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4981","last_page":"4985"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.39480000734329224,"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":0.39480000734329224,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.25780001282691956,"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":0.13210000097751617,"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/embedding","display_name":"Embedding","score":0.8127999901771545},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6096000075340271},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5324000120162964},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4975999891757965},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.42649999260902405},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.41819998621940613},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.40619999170303345},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.3930000066757202},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.38920000195503235}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.8127999901771545},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7806000113487244},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6725000143051147},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6184999942779541},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6096000075340271},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5324000120162964},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4975999891757965},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.42649999260902405},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.41819998621940613},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.40619999170303345},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3930000066757202},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.38920000195503235},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.3612000048160553},{"id":"https://openalex.org/C86827895","wikidata":"https://www.wikidata.org/wiki/Q7098582","display_name":"Opportunistic reasoning","level":4,"score":0.34549999237060547},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.32760000228881836},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.31940001249313354},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.31119999289512634},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.27230000495910645},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2671000063419342},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C43971567","wikidata":"https://www.wikidata.org/wiki/Q3142865","display_name":"Logical reasoning","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746252.3760855","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746252.3760855","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3746252.3760855","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":{"id":"doi:10.1145/3746252.3760855","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746252.3760855","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3746252.3760855","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416078617.pdf","grobid_xml":"https://content.openalex.org/works/W4416078617.grobid-xml"},"referenced_works_count":10,"referenced_works":["https://openalex.org/W4365129631","https://openalex.org/W4389518671","https://openalex.org/W4401043457","https://openalex.org/W4401248343","https://openalex.org/W4402672004","https://openalex.org/W4403577761","https://openalex.org/W4410987181","https://openalex.org/W4411584604","https://openalex.org/W4412164527","https://openalex.org/W4412889979"],"related_works":[],"abstract_inverted_index":{"Transformer-based":[0],"models":[1,42],"such":[2],"as":[3],"BERT":[4],"and":[5,66],"E5":[6],"have":[7],"significantly":[8,140],"advanced":[9],"text":[10,97],"embedding":[11,59,98,109,156],"by":[12,111],"capturing":[13],"rich":[14],"contextual":[15,64],"representations.":[16],"However,":[17],"many":[18],"complex":[19],"real-world":[20],"queries":[21],"require":[22],"sophisticated":[23],"reasoning":[24,48,72,94,114,153],"to":[25],"retrieve":[26],"relevant":[27],"documents":[28],"beyond":[29],"surface-level":[30],"lexical":[31],"matching,":[32],"where":[33],"encoder-only":[34],"retrievers":[35],"often":[36],"fall":[37],"short.":[38],"Decoder-only":[39],"large":[40],"language":[41,107],"(LLMs),":[43],"known":[44],"for":[45],"their":[46],"strong":[47],"capabilities,":[49],"offer":[50],"a":[51,86,133],"promising":[52],"alternative.":[53],"Despite":[54],"this":[55,78],"potential,":[56],"existing":[57,106],"LLM-based":[58],"methods":[60],"primarily":[61],"focus":[62],"on":[63,131],"representation":[65],"do":[67],"not":[68],"fully":[69],"exploit":[70],"the":[71,96,117,149,155],"strength":[73],"of":[74,151],"LLMs.":[75,102],"To":[76],"bridge":[77],"gap,":[79],"we":[80],"propose":[81],"Reasoning-Infused":[82],"Text":[83],"Embedding":[84],"(RITE),":[85],"simple":[87],"but":[88],"effective":[89],"approach":[90],"that":[91,138],"integrates":[92],"logical":[93],"into":[95,154],"process":[99],"using":[100],"generative":[101],"RITE":[103,139],"builds":[104],"upon":[105],"model":[108],"techniques":[110],"generating":[112],"intermediate":[113],"texts":[115],"in":[116],"token":[118],"space":[119],"before":[120],"computing":[121],"embeddings,":[122],"thereby":[123],"enriching":[124],"representations":[125],"with":[126],"inferential":[127],"depth.":[128],"Experimental":[129],"results":[130],"BRIGHT,":[132],"reasoning-intensive":[134],"retrieval":[135,143],"benchmark,":[136],"demonstrate":[137],"enhances":[141],"zero-shot":[142],"performance":[144],"across":[145],"diverse":[146],"domains,":[147],"underscoring":[148],"effectiveness":[150],"incorporating":[152],"process.":[157]},"counts_by_year":[],"updated_date":"2026-03-10T14:07:55.174380","created_date":"2025-11-10T00:00:00"}