{"id":"https://openalex.org/W3195945007","doi":"https://doi.org/10.1145/3447548.3470803","title":"From Deep Learning to Deep Reasoning","display_name":"From Deep Learning to Deep Reasoning","publication_year":2021,"publication_date":"2021-08-12","ids":{"openalex":"https://openalex.org/W3195945007","doi":"https://doi.org/10.1145/3447548.3470803","mag":"3195945007"},"language":"en","primary_location":{"id":"doi:10.1145/3447548.3470803","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3470803","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/conference_contribution/From_Deep_Learning_to_Deep_Reasoning/20645706","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085471517","display_name":"Truyen Tran","orcid":"https://orcid.org/0000-0001-6531-8907"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Truyen Tran","raw_affiliation_strings":["Deakin University, Waurn Ponds, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Deakin University, Waurn Ponds, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029157904","display_name":"Vuong Le","orcid":"https://orcid.org/0000-0003-1582-1269"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Vuong Le","raw_affiliation_strings":["Deakin University, Waurn Ponds, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Deakin University, Waurn Ponds, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101936199","display_name":"Hung L\u00ea","orcid":"https://orcid.org/0000-0002-3126-184X"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hung Le","raw_affiliation_strings":["Deakin University, Waurn Ponds, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Deakin University, Waurn Ponds, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079045166","display_name":"Thao Minh Le","orcid":"https://orcid.org/0000-0002-8089-9962"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Thao M. Le","raw_affiliation_strings":["Deakin University, Waurn Ponds, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Deakin University, Waurn Ponds, Australia","institution_ids":["https://openalex.org/I149704539"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149704539"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2019","issue":null,"first_page":"4076","last_page":"4077"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9983999729156494,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9983999729156494,"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":0.995199978351593,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9944000244140625,"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/computer-science","display_name":"Computer science","score":0.7632642984390259},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.65399169921875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6523140668869019},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6498991250991821},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.60072922706604},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.45978620648384094},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4514434039592743},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4511439800262451},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3861427307128906},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3793206810951233},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.13300547003746033}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7632642984390259},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.65399169921875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6523140668869019},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6498991250991821},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.60072922706604},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.45978620648384094},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4514434039592743},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4511439800262451},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3861427307128906},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3793206810951233},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.13300547003746033},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3447548.3470803","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3470803","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:dro.deakin.edu.au:DU:30156019","is_oa":false,"landing_page_url":"http://doi.org/10.1145/3447548.3470803","pdf_url":null,"source":{"id":"https://openalex.org/S4306401102","display_name":"Own your potential (DEAKIN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149704539","host_organization_name":"Deakin University","host_organization_lineage":["https://openalex.org/I149704539"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"},{"id":"pmh:oai:figshare.com:article/20645706","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/From_Deep_Learning_to_Deep_Reasoning/20645706","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference contribution"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/20645706","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/From_Deep_Learning_to_Deep_Reasoning/20645706","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference contribution"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W923655057","https://openalex.org/W2004652576","https://openalex.org/W2095739681","https://openalex.org/W2122193844","https://openalex.org/W2551396370","https://openalex.org/W2624614404","https://openalex.org/W2752099845","https://openalex.org/W2760103357","https://openalex.org/W2896457183","https://openalex.org/W2930003055","https://openalex.org/W2963223524","https://openalex.org/W2963403868","https://openalex.org/W2963693726","https://openalex.org/W2963858333","https://openalex.org/W2963870701","https://openalex.org/W2963920355","https://openalex.org/W2964118342","https://openalex.org/W2965310593","https://openalex.org/W2990397898","https://openalex.org/W2996131066","https://openalex.org/W3005814241","https://openalex.org/W3034513622","https://openalex.org/W3035393139","https://openalex.org/W3089358914"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"The":[0,161,167,199,220,231],"rise":[1],"of":[2,16,24,36,104,117,154,159,164],"big":[3,6],"data":[4,43,64,132,146],"and":[5,38,65,174,214,217,226,242],"compute":[7],"has":[8],"brought":[9],"modern":[10],"neural":[11,51,69,118,177,208,224],"networks":[12,52,70,119,178,209],"to":[13,20,30,47,56,73,80,82,98,113,120,128,142,236],"many":[14],"walks":[15],"digital":[17],"life,":[18],"thanks":[19],"the":[21,31,96,105,115,125,131,152,171],"relative":[22],"ease":[23],"constructing":[25],"large":[26],"models":[27],"that":[28,49],"scale":[29],"real":[32],"world.":[33],"Current":[34],"successes":[35],"Transformers":[37],"self-supervised":[39],"pretraining":[40],"on":[41,206],"massive":[42],"have":[44,62],"led":[45],"some":[46],"believe":[48],"deep":[50],"will":[53],"be":[54],"able":[55],"do":[57],"almost":[58],"everything":[59],"once":[60],"we":[61],"sufficient":[63],"computational":[66,197],"resources.":[67],"However,":[68],"are":[71,89],"fast":[72],"exploit":[74],"surface":[75],"statistics":[76],"but":[77],"fail":[78],"miserably":[79],"generalize":[81],"novel":[83,237],"combinations.":[84],"This":[85,108,136],"is":[86,127],"because":[87],"they":[88],"not":[90],"designed":[91],"for":[92,185],"deliberate":[93],"reasoning":[94,186,211],"--":[95],"capacity":[97,116,137],"deliberately":[99],"deduce":[100],"new":[101,140],"knowledge":[102],"out":[103],"contextualized":[106],"data.":[107],"tutorial":[109,162],"reviews":[110,223],"recent":[111],"developments":[112],"extend":[114],"\"learning-to-reason''":[121],"from":[122,145],"data,":[123,216],"where":[124],"task":[126],"determine":[129],"if":[130],"entails":[133],"a":[134,156,182],"conclusion.":[135],"opens":[138],"up":[139],"ways":[141],"generate":[143],"insights":[144],"through":[147,187],"arbitrary":[148],"compositional":[149],"querying":[150],"without":[151],"need":[153],"predefining":[155],"narrow":[157],"set":[158],"tasks.":[160],"consists":[163],"four":[165],"parts.":[166],"first":[168],"part":[169,201,222,233],"covers":[170],"learning-to-reason":[172],"framework,":[173],"explains":[175],"how":[176,207],"can":[179],"serve":[180],"as":[181,192],"strong":[183],"backbone":[184],"its":[188],"natural":[189],"operations":[190],"such":[191],"binding,":[193],"attention":[194],"&":[195],"dynamic":[196],"graphs.":[198],"second":[200],"goes":[202],"into":[203],"more":[204,244],"detail":[205],"perform":[210],"over":[212],"unstructured":[213],"structured":[215],"across":[218],"modalities.":[219],"third":[221],"memories":[225],"their":[227],"role":[228],"in":[229],"reasoning.":[230],"last":[232],"discusses":[234],"generalization":[235],"combinations,":[238],"under":[239],"less":[240],"supervision":[241],"with":[243],"knowledge.":[245]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}