{"id":"https://openalex.org/W2275025625","doi":"https://doi.org/10.1109/taslp.2015.2509257","title":"Adaptive Multi-Compositionality for Recursive Neural Network Models","display_name":"Adaptive Multi-Compositionality for Recursive Neural Network Models","publication_year":2015,"publication_date":"2015-12-17","ids":{"openalex":"https://openalex.org/W2275025625","doi":"https://doi.org/10.1109/taslp.2015.2509257","mag":"2275025625"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2015.2509257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2015.2509257","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-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/A5100407387","display_name":"Dong Li","orcid":"https://orcid.org/0000-0001-9336-0694"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Li Dong","raw_affiliation_strings":["SKLSDE, University of Edinburgh, Edinburgh, China"],"affiliations":[{"raw_affiliation_string":"SKLSDE, University of Edinburgh, Edinburgh, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014662947","display_name":"Furu Wei","orcid":"https://orcid.org/0000-0002-7810-5852"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Furu Wei","raw_affiliation_strings":["Microsoft Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107234003","display_name":"Ke Xu","orcid":"https://orcid.org/0000-0001-5447-8008"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Xu","raw_affiliation_strings":["State Key Laboratory of Software Development Environment, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Software Development Environment, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shixia Liu","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":"Shixia Liu","raw_affiliation_strings":["School of Software, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100701572","display_name":"Ming Zhou","orcid":"https://orcid.org/0000-0002-2551-2964"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Zhou","raw_affiliation_strings":["Microsoft Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100407387"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3354,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.86988557,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"24","issue":"3","first_page":"422","last_page":"431"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":1.0,"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/T10181","display_name":"Natural Language Processing Techniques","score":1.0,"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/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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/T13629","display_name":"Text Readability and Simplification","score":0.9839000105857849,"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/principle-of-compositionality","display_name":"Principle of compositionality","score":0.8562433123588562},{"id":"https://openalex.org/keywords/treebank","display_name":"Treebank","score":0.8310928344726562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8065645694732666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6382884979248047},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5833607316017151},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5740365982055664},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5279504656791687},{"id":"https://openalex.org/keywords/composition","display_name":"Composition (language)","score":0.443266898393631},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4389650821685791},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4377167224884033},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.42752718925476074},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.42292076349258423},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3757742643356323},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.07531771063804626}],"concepts":[{"id":"https://openalex.org/C121375916","wikidata":"https://www.wikidata.org/wiki/Q936559","display_name":"Principle of compositionality","level":2,"score":0.8562433123588562},{"id":"https://openalex.org/C206134035","wikidata":"https://www.wikidata.org/wiki/Q811525","display_name":"Treebank","level":3,"score":0.8310928344726562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8065645694732666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6382884979248047},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5833607316017151},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5740365982055664},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5279504656791687},{"id":"https://openalex.org/C40231798","wikidata":"https://www.wikidata.org/wiki/Q1333743","display_name":"Composition (language)","level":2,"score":0.443266898393631},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4389650821685791},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4377167224884033},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.42752718925476074},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.42292076349258423},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3757742643356323},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.07531771063804626},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taslp.2015.2509257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2015.2509257","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G8055127673","display_name":null,"funder_award_id":"61421003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W42251416","https://openalex.org/W233613663","https://openalex.org/W1423339008","https://openalex.org/W1484288670","https://openalex.org/W1498436455","https://openalex.org/W1608322251","https://openalex.org/W1662133657","https://openalex.org/W1889268436","https://openalex.org/W1983578042","https://openalex.org/W1984052055","https://openalex.org/W2013494846","https://openalex.org/W2051390224","https://openalex.org/W2091378168","https://openalex.org/W2095168618","https://openalex.org/W2097606805","https://openalex.org/W2104518905","https://openalex.org/W2117130368","https://openalex.org/W2124824117","https://openalex.org/W2125573226","https://openalex.org/W2127002961","https://openalex.org/W2133280805","https://openalex.org/W2154359981","https://openalex.org/W2163455955","https://openalex.org/W2181042685","https://openalex.org/W2251939518","https://openalex.org/W2977947870","https://openalex.org/W3099386342","https://openalex.org/W3197748241","https://openalex.org/W6601760448","https://openalex.org/W6609063932","https://openalex.org/W6628124331","https://openalex.org/W6629004733","https://openalex.org/W6636221068","https://openalex.org/W6639364127","https://openalex.org/W6678519443","https://openalex.org/W6678656546","https://openalex.org/W6679915538","https://openalex.org/W6682839988","https://openalex.org/W6685683567","https://openalex.org/W6691459498","https://openalex.org/W6768268988","https://openalex.org/W6801561724"],"related_works":["https://openalex.org/W3142119062","https://openalex.org/W2740662036","https://openalex.org/W159209093","https://openalex.org/W589103562","https://openalex.org/W1991220724","https://openalex.org/W2251234095","https://openalex.org/W131522978","https://openalex.org/W2250768577","https://openalex.org/W2251939518","https://openalex.org/W2795843251"],"abstract_inverted_index":{"Recursive":[0],"neural":[1,55,118,146],"network":[2,56,119,147],"models":[3,19,120,148],"have":[4],"achieved":[5],"promising":[6],"results":[7,137],"in":[8,21],"many":[9],"natural":[10],"language":[11],"processing":[12],"tasks.":[13,111],"The":[14,58,94,135],"main":[15],"difference":[16],"among":[17],"these":[18,91],"lies":[20],"the":[22,29,38,84,107,126,142,151],"composition":[23,67,86,92,95],"function,":[24],"i.e.,":[25],"how":[26],"to":[27,53,62,82],"obtain":[28],"vector":[30],"representation":[31],"for":[32,100],"a":[33,47,79,88],"phrase":[34],"or":[35],"sentence":[36],"using":[37],"representations":[39],"of":[40,90,109,144],"words":[41],"it":[42],"contains.":[43],"This":[44],"paper":[45],"introduces":[46],"novel":[48],"Adaptive":[49],"Multi-Compositionality":[50],"(AdaMC)":[51],"layer":[52],"recursive":[54,117,145],"models.":[57],"basic":[59],"idea":[60],"is":[61],"use":[63],"more":[64],"than":[65],"one":[66],"function":[68],"and":[69,97,121,130,149],"adaptively":[70],"select":[71],"them":[72],"depending":[73],"on":[74,125],"input":[75],"vectors.":[76],"We":[77,112],"develop":[78],"general":[80],"framework":[81],"model":[83],"semantic":[85,131],"as":[87],"distribution":[89],"functions.":[93],"functions":[96],"parameters":[98],"used":[99],"adaptive":[101],"selection":[102],"are":[103],"jointly":[104],"learnt":[105],"from":[106],"supervision":[108],"specific":[110],"integrate":[113],"AdaMC":[114,140],"into":[115],"existing":[116],"conduct":[122],"extensive":[123],"experiments":[124],"Stanford":[127],"Sentiment":[128],"Treebank":[129],"relation":[132],"classification":[133],"task.":[134],"experimental":[136],"demonstrate":[138],"that":[139],"improves":[141],"performance":[143],"outperforms":[150],"baseline":[152],"methods.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
