{"id":"https://openalex.org/W4387846608","doi":"https://doi.org/10.1145/3583780.3615197","title":"POSPAN: Position-Constrained Span Masking for Language Model Pre-training","display_name":"POSPAN: Position-Constrained Span Masking for Language Model Pre-training","publication_year":2023,"publication_date":"2023-10-21","ids":{"openalex":"https://openalex.org/W4387846608","doi":"https://doi.org/10.1145/3583780.3615197"},"language":"en","primary_location":{"id":"doi:10.1145/3583780.3615197","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583780.3615197","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Information and Knowledge Management","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/A5018294563","display_name":"Zhenyu Zhang","orcid":"https://orcid.org/0009-0005-7851-3425"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhenyu Zhang","raw_affiliation_strings":["JD AI Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"JD AI Research, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027658278","display_name":"Lei Shen","orcid":"https://orcid.org/0000-0003-0307-696X"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Shen","raw_affiliation_strings":["JD AI Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"JD AI Research, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120313471","display_name":"Yuming Zhao","orcid":"https://orcid.org/0009-0005-5582-9240"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuming Zhao","raw_affiliation_strings":["JD AI Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"JD AI Research, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115621122","display_name":"Meng Chen","orcid":"https://orcid.org/0009-0006-9908-4524"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Chen","raw_affiliation_strings":["JD AI Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"JD AI Research, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101727205","display_name":"Xiaodong He","orcid":"https://orcid.org/0000-0002-9463-9168"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong He","raw_affiliation_strings":["JD AI Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"JD AI Research, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5018294563"],"corresponding_institution_ids":["https://openalex.org/I4210103986"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1396975,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"668","issue":null,"first_page":"4420","last_page":"4424"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9998000264167786,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9872999787330627,"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/span","display_name":"Span (engineering)","score":0.8078783750534058},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.7732006311416626},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7483235597610474},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.7391549348831177},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.7192552089691162},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.6557432413101196},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5699183344841003},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46134430170059204},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.35969069600105286},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3359450399875641},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13834214210510254},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08120158314704895}],"concepts":[{"id":"https://openalex.org/C2778753569","wikidata":"https://www.wikidata.org/wiki/Q1960395","display_name":"Span (engineering)","level":2,"score":0.8078783750534058},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.7732006311416626},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7483235597610474},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.7391549348831177},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.7192552089691162},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.6557432413101196},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5699183344841003},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46134430170059204},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.35969069600105286},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3359450399875641},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13834214210510254},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08120158314704895},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","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":1,"locations":[{"id":"doi:10.1145/3583780.3615197","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583780.3615197","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8299999833106995}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2606964149","https://openalex.org/W2963323070","https://openalex.org/W2997200074","https://openalex.org/W3011411500","https://openalex.org/W3034238904","https://openalex.org/W3034878914","https://openalex.org/W3034999214","https://openalex.org/W3104453885","https://openalex.org/W3171291687","https://openalex.org/W3209091012","https://openalex.org/W3210120707","https://openalex.org/W3213368993","https://openalex.org/W4246649926","https://openalex.org/W4252110927","https://openalex.org/W6802852670"],"related_works":["https://openalex.org/W4388335561","https://openalex.org/W2970530566","https://openalex.org/W4288261899","https://openalex.org/W4307309205","https://openalex.org/W2967478618","https://openalex.org/W4385009901","https://openalex.org/W4385572700","https://openalex.org/W2997152889","https://openalex.org/W4387768015","https://openalex.org/W4285141722"],"abstract_inverted_index":{"Span-level":[0],"masked":[1,52,146],"language":[2,12,27,147],"modeling":[3],"(MLM)":[4],"has":[5],"shown":[6],"to":[7,10,26,66,149],"be":[8],"advantageous":[9],"pre-trained":[11],"models":[13,148],"over":[14],"the":[15,40,49,74,93,103,113,142,153,160],"original":[16],"single-token":[17],"MLM,":[18],"as":[19],"entities/phrases":[20],"and":[21,80,123,133,162],"their":[22],"dependencies":[23,41],"are":[24,44,54],"critical":[25],"understanding.":[28],"Previous":[29],"works":[30,157],"only":[31],"consider":[32],"span":[33,70,77],"length":[34,78],"with":[35],"some":[36],"discrete":[37],"distributions,":[38],"while":[39],"among":[42],"spans":[43,53],"ignored,":[45],"i.e.,":[46],"assuming":[47],"that":[48,112],"positions":[50],"of":[51,76,95,118,164],"uniformly":[55],"distributed.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60,99],"present":[61],"POSPAN,":[62],"a":[63],"general":[64],"framework":[65],"allow":[67],"diverse":[68],"position-constrained":[69],"masking":[71,89,121],"strategies":[72],"via":[73],"combination":[75],"distribution":[79],"position":[81,114,143],"constraint":[82,115,144],"distribution,":[83],"which":[84],"unifies":[85],"all":[86],"existing":[87],"span-level":[88,120],"methods.":[90],"To":[91],"verify":[92],"effectiveness":[94],"POSPAN":[96,126,156],"in":[97,145],"pre-training,":[98],"evaluate":[100],"it":[101],"on":[102,152],"datasets":[104],"from":[105],"several":[106],"NLU":[107],"benchmarks.":[108],"Experimental":[109],"results":[110],"indicate":[111],"is":[116],"capable":[117],"enhancing":[119],"broadly,":[122],"our":[124],"best":[125],"setting":[127],"consistently":[128],"outperforms":[129],"its":[130],"span-length-only":[131],"counterparts":[132],"vanilla":[134],"MLM.":[135],"We":[136],"also":[137],"conduct":[138],"theoretical":[139],"analysis":[140],"for":[141],"shed":[150],"light":[151],"reason":[154],"why":[155],"well,":[158],"demonstrating":[159],"rationality":[161],"necessity":[163],"POSPAN.":[165]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}