{"id":"https://openalex.org/W7124676279","doi":"https://doi.org/10.1145/3789203","title":"Improving Pseudo-Labeling by Dynamic Confidence Calibration for Semi-Supervised Sequence Recognition","display_name":"Improving Pseudo-Labeling by Dynamic Confidence Calibration for Semi-Supervised Sequence Recognition","publication_year":2026,"publication_date":"2026-01-19","ids":{"openalex":"https://openalex.org/W7124676279","doi":"https://doi.org/10.1145/3789203"},"language":"en","primary_location":{"id":"doi:10.1145/3789203","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3789203","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","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":null,"display_name":"Keke Xu","orcid":"https://orcid.org/0000-0001-9300-7284"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keke Xu","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9300-7284","affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123339805","display_name":"Zhenghua Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenghua Peng","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6827-9253","affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shuangping Huang","orcid":"https://orcid.org/0000-0002-5544-4544"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuangping Huang","raw_affiliation_strings":["South China University of Technology, Guangzhou, China and Pazhou Laboratory Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5544-4544","affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China and Pazhou Laboratory Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Gege Zhang","orcid":"https://orcid.org/0009-0002-3193-2073"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gege Zhang","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0002-3193-2073","affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118122843","display_name":"Yunqing Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yunqing Hu","raw_affiliation_strings":["Zhuzhou CRRC Times Electric Co. Ltd., Zhuzhou, China"],"raw_orcid":"https://orcid.org/0009-0004-2611-3166","affiliations":[{"raw_affiliation_string":"Zhuzhou CRRC Times Electric Co. Ltd., Zhuzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121776382","display_name":"Wenjie Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjie Peng","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3442-558X","affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":19.5563,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.9754094,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"22","issue":"3","first_page":"1","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.2980000078678131,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.2980000078678131,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.1736000031232834,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.09200000017881393,"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/overconfidence-effect","display_name":"Overconfidence effect","score":0.9132000207901001},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6402000188827515},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5221999883651733},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.4472000002861023},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.3991999924182892},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.3815000057220459},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.3765000104904175}],"concepts":[{"id":"https://openalex.org/C51110983","wikidata":"https://www.wikidata.org/wiki/Q16503490","display_name":"Overconfidence effect","level":2,"score":0.9132000207901001},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8514000177383423},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6402000188827515},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6154999732971191},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5494999885559082},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5221999883651733},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.4472000002861023},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.3991999924182892},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.3815000057220459},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.3765000104904175},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.36809998750686646},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.36550000309944153},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.3513000011444092},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3513000011444092},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2624000012874603},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2563000023365021},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3789203","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3789203","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1971822075","https://openalex.org/W1998042868","https://openalex.org/W2008806374","https://openalex.org/W2049951199","https://openalex.org/W2144554289","https://openalex.org/W2146835493","https://openalex.org/W2152928267","https://openalex.org/W2343052201","https://openalex.org/W2809273748","https://openalex.org/W2914492226","https://openalex.org/W2963242190","https://openalex.org/W2963327605","https://openalex.org/W2963351448","https://openalex.org/W2979382951","https://openalex.org/W2988326850","https://openalex.org/W3004846386","https://openalex.org/W3151142710","https://openalex.org/W3177684257","https://openalex.org/W3181186176","https://openalex.org/W3202415716","https://openalex.org/W4225562651","https://openalex.org/W4307640249","https://openalex.org/W4310255432","https://openalex.org/W4312560592","https://openalex.org/W4312879041","https://openalex.org/W4372260363","https://openalex.org/W4376105196","https://openalex.org/W4376647170","https://openalex.org/W4386410320","https://openalex.org/W4387343643","https://openalex.org/W4387587607","https://openalex.org/W4389060483","https://openalex.org/W4391931509","https://openalex.org/W4396877736","https://openalex.org/W4403996998","https://openalex.org/W4404694933","https://openalex.org/W4406047244","https://openalex.org/W4406240400"],"related_works":[],"abstract_inverted_index":{"Sequence":[0],"recognition":[1,76,236],"models":[2,77],"under":[3],"a":[4,85,126,159,198],"fully":[5],"supervised":[6],"paradigm":[7],"require":[8],"large-scale":[9],"training":[10,118],"data,":[11],"incurring":[12],"substantial":[13],"annotation":[14,231],"costs.":[15],"Pseudo-labeling":[16],"is":[17,50,78],"one":[18],"of":[19,47,84,137,154,225],"the":[20,45,56,72,81,88,98,105,116,135,138,143,152,172,181,187,192,204,209,212,221],"most":[21],"effective":[22],"techniques":[23],"in":[24,74,104],"semi-supervised":[25,48,117,193,215],"learning,":[26],"which":[27,228],"leverages":[28],"predicted":[29,57],"confidence":[30],"to":[31,94,141,150,170,185,202],"filter":[32,61],"pseudo-labels":[33],"on":[34],"unlabeled":[35],"data":[36],"for":[37,208],"model":[38,173],"training.":[39,65],"However,":[40],"recent":[41],"studies":[42],"indicate":[43],"that":[44,71,101,133,164],"performance":[46],"learning":[49,194,216],"compromised":[51],"by":[52,80,147],"overconfident":[53,148,179],"models,":[54],"as":[55,97],"unreliable":[58],"confidences":[59],"will":[60],"noisy":[62],"samples":[63],"into":[64],"In":[66],"this":[67,111,122],"work,":[68],"we":[69,124,157,196],"discover":[70],"overconfidence":[73,112,136,188],"sequence":[75],"influenced":[79],"linguistic":[82],"properties":[83],"sequence,":[86],"where":[87],"tail":[89],"character":[90],"classes":[91],"are":[92],"prone":[93],"be":[95],"mispredicted":[96],"head":[99,139,182],"ones":[100],"frequently":[102],"appear":[103],"language":[106],"with":[107],"high":[108],"confidence.":[109],"And":[110],"continuously":[113],"intensifies":[114],"throughout":[115,191],"process.":[119],"To":[120],"address":[121,186],"limitation,":[123],"propose":[125],"Dynamic":[127],"Sequential":[128],"Class-Aware":[129],"Smoothing":[130],"(DSCS)":[131],"method":[132],"calibrates":[134],"class":[140,167],"alleviate":[142],"inaccurate":[144],"pseudo-labeling":[145],"caused":[146],"misprediction":[149],"improve":[151],"quality":[153],"pseudo-labels.":[155],"Specifically,":[156],"design":[158],"sequential":[160],"class-aware":[161],"smoothing":[162],"module":[163,201],"incorporates":[165],"token":[166],"frequency":[168],"information":[169],"regularize":[171],"and":[174,214,223],"prevent":[175],"it":[176],"from":[177],"becoming":[178],"toward":[180],"class.":[183],"Meanwhile,":[184],"problem":[189],"intensifying":[190],"processes,":[195],"introduce":[197],"dynamic":[199],"regularization":[200],"adjust":[203],"calibration":[205,213],"strength":[206],"dynamically":[207],"coordination":[210],"between":[211],"processes.":[217],"Extensive":[218],"experiments":[219],"demonstrate":[220],"effectiveness":[222],"generality":[224],"our":[226],"method,":[227],"significantly":[229],"reduces":[230],"efforts":[232],"while":[233],"maintaining":[234],"competitive":[235],"performance.":[237]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-20T00:00:00"}