{"id":"https://openalex.org/W4320732432","doi":"https://doi.org/10.48550/arxiv.2210.07988","title":"PseudoReasoner: Leveraging Pseudo Labels for Commonsense Knowledge Base Population","display_name":"PseudoReasoner: Leveraging Pseudo Labels for Commonsense Knowledge Base Population","publication_year":2022,"publication_date":"2022-10-14","ids":{"openalex":"https://openalex.org/W4320732432","doi":"https://doi.org/10.48550/arxiv.2210.07988"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2210.07988","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.07988","pdf_url":"https://arxiv.org/pdf/2210.07988","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2210.07988","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046409172","display_name":"Tianqing Fang","orcid":"https://orcid.org/0000-0002-0186-8253"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Fang, Tianqing","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072943891","display_name":"Quyet V. Do","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Do, Quyet V.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100445028","display_name":"Hongming Zhang","orcid":"https://orcid.org/0000-0001-8172-6484"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Hongming","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020880385","display_name":"Yangqiu Song","orcid":"https://orcid.org/0000-0002-7818-6090"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Yangqiu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051502105","display_name":"Ginny Y. Wong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wong, Ginny Y.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5077539496","display_name":"Simon See","orcid":"https://orcid.org/0000-0002-4958-9237"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"See, Simon","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5046409172"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9958000183105469,"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":0.9958000183105469,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9793999791145325,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9688000082969666,"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/discriminative-model","display_name":"Discriminative model","score":0.801140546798706},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.721808671951294},{"id":"https://openalex.org/keywords/commonsense-reasoning","display_name":"Commonsense reasoning","score":0.6591384410858154},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6558142900466919},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.625849723815918},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6083411574363708},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5928323268890381},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5622414946556091},{"id":"https://openalex.org/keywords/commonsense-knowledge","display_name":"Commonsense knowledge","score":0.50993812084198},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5000624656677246},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4836181700229645},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4702771008014679},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.4568330943584442},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.42081180214881897},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.4198686182498932},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.37851470708847046},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.37832966446876526},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08301860094070435}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.801140546798706},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.721808671951294},{"id":"https://openalex.org/C193221554","wikidata":"https://www.wikidata.org/wiki/Q5153664","display_name":"Commonsense reasoning","level":2,"score":0.6591384410858154},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6558142900466919},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.625849723815918},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6083411574363708},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5928323268890381},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5622414946556091},{"id":"https://openalex.org/C30542707","wikidata":"https://www.wikidata.org/wiki/Q1603203","display_name":"Commonsense knowledge","level":3,"score":0.50993812084198},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5000624656677246},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4836181700229645},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4702771008014679},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.4568330943584442},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.42081180214881897},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.4198686182498932},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37851470708847046},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.37832966446876526},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08301860094070435},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:2210.07988","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.07988","pdf_url":"https://arxiv.org/pdf/2210.07988","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-125545","is_oa":false,"landing_page_url":"http://lbdiscover.ust.hk/uresolver?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rfr_id=info:sid/HKUST:SPI&rft.genre=article&rft.issn=&rft.volume=&rft.issue=&rft.date=2022&rft.spage=&rft.aulast=Fang&rft.aufirst=Tianqing&rft.atitle=PseudoReasoner%3A+Leveraging+Pseudo+Labels+for+Commonsense+Knowledge+Base+Population&rft.title=","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"},{"id":"doi:10.48550/arxiv.2210.07988","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2210.07988","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2210.07988","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.07988","pdf_url":"https://arxiv.org/pdf/2210.07988","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6600000262260437,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3035583586","https://openalex.org/W4320165839","https://openalex.org/W2151799802","https://openalex.org/W4385488510","https://openalex.org/W2196562041","https://openalex.org/W2073302931","https://openalex.org/W3206107299","https://openalex.org/W3082691151","https://openalex.org/W4287633646","https://openalex.org/W4378501473"],"abstract_inverted_index":{"Commonsense":[0],"Knowledge":[1],"Base":[2],"(CSKB)":[3],"Population":[4],"aims":[5],"at":[6,165],"reasoning":[7,22],"over":[8],"unseen":[9],"entities":[10],"and":[11,15,122,148,156,161],"assertions":[12],"on":[13,73,79,119,144,152],"CSKBs,":[14],"is":[16,26,39,53],"an":[17],"important":[18],"yet":[19],"hard":[20],"commonsense":[21],"task.":[23],"One":[24],"challenge":[25],"that":[27,67],"it":[28],"requires":[29],"out-of-domain":[30,154],"generalization":[31],"ability":[32],"as":[33,104],"the":[34,47,80,123,130,136,145,153,158],"source":[35],"CSKB":[36,65],"for":[37,51,64,84,115],"training":[38],"of":[40],"a":[41,60,69,85,95,111],"relatively":[42],"smaller":[43],"scale":[44],"(1M)":[45],"while":[46],"whole":[48],"candidate":[49,82],"space":[50],"population":[52,66],"way":[54],"larger":[55],"(200M).":[56],"We":[57],"propose":[58],"PseudoReasoner,":[59],"semi-supervised":[61],"learning":[62],"framework":[63,133],"uses":[68],"teacher":[70,92],"model":[71,87,97,138],"pre-trained":[72],"CSKBs":[74],"to":[75,88,101,127],"provide":[76],"pseudo":[77,116],"labels":[78,117],"unlabeled":[81],"dataset":[83],"student":[86,124],"learn":[89],"from.":[90],"The":[91,132],"can":[93,134],"be":[94],"generative":[96],"rather":[98],"than":[99],"restricted":[100],"discriminative":[102],"models":[103],"previous":[105],"works.":[106],"In":[107],"addition,":[108],"we":[109],"design":[110],"new":[112],"filtering":[113],"procedure":[114],"based":[118],"influence":[120],"function":[121],"model's":[125],"prediction":[126],"further":[128],"improve":[129,135],"performance.":[131],"backbone":[137],"KG-BERT":[139],"(RoBERTa-large)":[140],"by":[141],"3.3":[142],"points":[143,151],"overall":[146],"performance":[147],"especially,":[149],"5.3":[150],"performance,":[155],"achieves":[157],"state-of-the-art.":[159],"Codes":[160],"data":[162],"are":[163],"available":[164],"https://github.com/HKUST-KnowComp/PseudoReasoner.":[166]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}