{"id":"https://openalex.org/W4408355867","doi":"https://doi.org/10.1109/icassp49660.2025.10889603","title":"MAEM: A Multi-Aspect Extraction Model for Enhanced Embedding in RAG","display_name":"MAEM: A Multi-Aspect Extraction Model for Enhanced Embedding in RAG","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408355867","doi":"https://doi.org/10.1109/icassp49660.2025.10889603"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10889603","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5086059667","display_name":"Nengjun Yi","orcid":"https://orcid.org/0000-0001-5857-5868"},"institutions":[{"id":"https://openalex.org/I4210108629","display_name":"Computer Network Information Center","ror":"https://ror.org/01s0wyf50","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210108629"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ningyuan Yi","raw_affiliation_strings":["Chinese Academy of Sciences,Computer Network Information Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Computer Network Information Center,Beijing,China","institution_ids":["https://openalex.org/I4210108629","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100322151","display_name":"Chen Liu","orcid":"https://orcid.org/0000-0002-2819-704X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210108629","display_name":"Computer Network Information Center","ror":"https://ror.org/01s0wyf50","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210108629"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Liu","raw_affiliation_strings":["Chinese Academy of Sciences,Computer Network Information Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Computer Network Information Center,Beijing,China","institution_ids":["https://openalex.org/I4210108629","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100372035","display_name":"Yue Wang","orcid":"https://orcid.org/0000-0002-4603-3348"},"institutions":[{"id":"https://openalex.org/I4210108629","display_name":"Computer Network Information Center","ror":"https://ror.org/01s0wyf50","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210108629"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Wang","raw_affiliation_strings":["Chinese Academy of Sciences,Computer Network Information Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Computer Network Information Center,Beijing,China","institution_ids":["https://openalex.org/I4210108629","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103628693","display_name":"Jianjun Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108629","display_name":"Computer Network Information Center","ror":"https://ror.org/01s0wyf50","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210108629"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianjun Yu","raw_affiliation_strings":["Chinese Academy of Sciences,Computer Network Information Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Computer Network Information Center,Beijing,China","institution_ids":["https://openalex.org/I4210108629","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5086059667"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210108629"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02094757,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.22529999911785126,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.22529999911785126,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.210099995136261,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6899512410163879},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6563072800636292},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.5810409784317017},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3419920802116394},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.08252611756324768},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.06738096475601196}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6899512410163879},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6563072800636292},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5810409784317017},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3419920802116394},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.08252611756324768},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.06738096475601196}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10889603","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2052087587","https://openalex.org/W2064675550","https://openalex.org/W2998702515","https://openalex.org/W3099700870","https://openalex.org/W4290943593","https://openalex.org/W4312075150","https://openalex.org/W4316660679","https://openalex.org/W4385572770","https://openalex.org/W4387848842","https://openalex.org/W4389520259","https://openalex.org/W4392384362","https://openalex.org/W4400531953","https://openalex.org/W6810738896"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2081900870","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890"],"abstract_inverted_index":{"Retrieval":[0],"Augmented":[1],"Generation":[2],"can":[3],"effectively":[4],"reduce":[5],"hallucinations":[6],"in":[7,74],"LLMs":[8,78],"during":[9],"question-answering,":[10],"with":[11],"embedding":[12,20],"models":[13,21,119],"directly":[14],"influencing":[15],"its":[16],"performance.":[17],"While":[18],"current":[19],"improve":[22],"encoding":[23],"through":[24],"large-scale":[25],"training,":[26],"they":[27],"often":[28],"overlook":[29],"the":[30,37,44,81,86],"potential":[31],"or":[32],"explicit":[33],"multi-aspect":[34],"information":[35],"within":[36],"text.":[38],"To":[39],"address":[40],"this,":[41],"we":[42],"propose":[43],"Multi-Aspect":[45],"Extraction":[46],"Model":[47],"(MAEM),":[48],"an":[49],"eigen":[50],"decomposition-based":[51],"approach":[52],"that":[53],"extracts":[54],"and":[55,66,84,91,95,108],"integrates":[56],"text":[57],"aspects":[58],"into":[59,97],"a":[60,68,121],"unified":[61],"vector":[62],"for":[63],"enhanced":[64],"retrieval,":[65],"introduce":[67],"regularization":[69,96],"loss":[70],"function":[71],"to":[72,79,117],"assist":[73],"training.":[75],"We":[76],"utilized":[77],"create":[80],"Policy-Corpus":[82,90],"dataset":[83],"validated":[85],"model":[87],"on":[88,106,111],"both":[89],"FiQA.":[92],"Incorporating":[93],"MAEM":[94],"GTE<inf":[98],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[99],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">base</inf>":[100],"improved":[101],"NDCG@10":[102],"by":[103],"3.8":[104],"points":[105,110],"FiQA":[107],"4.56":[109],"Policy-Corpus.":[112],"Respectively,":[113],"achieving":[114],"results":[115],"comparable":[116],"larger":[118],"using":[120],"smaller":[122],"parameter":[123],"model.":[124]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}