{"id":"https://openalex.org/W4387848696","doi":"https://doi.org/10.1145/3583780.3615093","title":"Towards Spoken Language Understanding via Multi-level Multi-grained Contrastive Learning","display_name":"Towards Spoken Language Understanding via Multi-level Multi-grained Contrastive Learning","publication_year":2023,"publication_date":"2023-10-21","ids":{"openalex":"https://openalex.org/W4387848696","doi":"https://doi.org/10.1145/3583780.3615093"},"language":"en","primary_location":{"id":"doi:10.1145/3583780.3615093","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583780.3615093","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/A5018420548","display_name":"Xuxin Cheng","orcid":"https://orcid.org/0009-0002-6244-2931"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuxin Cheng","raw_affiliation_strings":["Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101767476","display_name":"Wanshi Xu","orcid":"https://orcid.org/0009-0004-3371-0137"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanshi Xu","raw_affiliation_strings":["Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102856192","display_name":"Zhihong Zhu","orcid":"https://orcid.org/0009-0001-4530-5516"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihong Zhu","raw_affiliation_strings":["Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017617498","display_name":"Hongxiang Li","orcid":"https://orcid.org/0009-0000-7710-8835"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxiang Li","raw_affiliation_strings":["Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034401157","display_name":"Yuexian Zou","orcid":"https://orcid.org/0000-0002-0144-1794"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuexian Zou","raw_affiliation_strings":["Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5018420548"],"corresponding_institution_ids":["https://openalex.org/I4210128628"],"apc_list":null,"apc_paid":null,"fwci":1.9011,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.88783024,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"326","last_page":"336"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","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/T12031","display_name":"Speech and dialogue systems","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/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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":0.994700014591217,"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":0.8952029347419739},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.7394850850105286},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.6319299936294556},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5651843547821045},{"id":"https://openalex.org/keywords/spoken-language","display_name":"Spoken language","score":0.5397845506668091},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5367397665977478},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5346217751502991},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4880741834640503},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4753175377845764}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8952029347419739},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.7394850850105286},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.6319299936294556},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5651843547821045},{"id":"https://openalex.org/C2776230583","wikidata":"https://www.wikidata.org/wiki/Q1322198","display_name":"Spoken language","level":2,"score":0.5397845506668091},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5367397665977478},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5346217751502991},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4880741834640503},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4753175377845764},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3583780.3615093","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583780.3615093","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":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7799999713897705}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1739072399","display_name":null,"funder_award_id":"62176008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2981938667","display_name":null,"funder_award_id":"Shenzhen","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G384178317","display_name":null,"funder_award_id":"02008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5939423041","display_name":null,"funder_award_id":"Technology","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8161904097","display_name":null,"funder_award_id":"202008","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":34,"referenced_works":["https://openalex.org/W648947103","https://openalex.org/W1971034924","https://openalex.org/W1975244201","https://openalex.org/W2077302143","https://openalex.org/W2094472029","https://openalex.org/W2127589108","https://openalex.org/W2162245945","https://openalex.org/W2473329891","https://openalex.org/W2474111273","https://openalex.org/W2551571666","https://openalex.org/W2595551253","https://openalex.org/W2599674900","https://openalex.org/W2803392141","https://openalex.org/W2804945011","https://openalex.org/W2899575547","https://openalex.org/W2946085385","https://openalex.org/W2962735107","https://openalex.org/W2963033987","https://openalex.org/W2963974889","https://openalex.org/W2965006690","https://openalex.org/W2970450228","https://openalex.org/W2971167298","https://openalex.org/W2979826702","https://openalex.org/W3099757670","https://openalex.org/W3101273072","https://openalex.org/W3161463965","https://openalex.org/W3170264707","https://openalex.org/W3173794693","https://openalex.org/W3193861091","https://openalex.org/W3209239055","https://openalex.org/W4224212267","https://openalex.org/W4225403296","https://openalex.org/W4283644197","https://openalex.org/W4385567178"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2529301793","https://openalex.org/W2378857091","https://openalex.org/W2384121599","https://openalex.org/W2999756192","https://openalex.org/W103652678","https://openalex.org/W2038083449","https://openalex.org/W157723669","https://openalex.org/W2284708545"],"abstract_inverted_index":{"Spoken":[0],"language":[1],"understanding":[2,15],"(SLU)":[3],"is":[4],"a":[5,79,162],"core":[6],"task":[7],"in":[8],"task-oriented":[9],"dialogue":[10],"systems,":[11],"which":[12],"aims":[13],"at":[14,89],"user's":[16],"current":[17],"goal":[18],"through":[19],"constructing":[20],"semantic":[21],"frames.":[22],"SLU":[23,39,82,159],"usually":[24],"consists":[25],"of":[26,52,138],"two":[27,44,71,156],"subtasks,":[28],"including":[29,92],"intent":[30,102],"detection":[31],"and":[32,46,61,63,97,103,121,143],"slot":[33,95,104],"filling.":[34],"Although":[35],"there":[36],"are":[37],"some":[38],"frameworks":[40],"joint":[41],"modeling":[42],"the":[43,48,56,70,75,111,131,136,139],"subtasks":[45],"achieve":[47,66],"high":[49],"performance,":[50],"most":[51],"them":[53],"still":[54],"overlook":[55],"inherent":[57],"relationships":[58],"between":[59,69],"intents":[60],"slots,":[62],"fail":[64],"to":[65,85,100,105,134,171],"mutual":[67],"guidance":[68],"subtasks.":[72],"To":[73],"solve":[74],"problem,":[76],"we":[77,128],"propose":[78],"multi-level":[80],"multi-grained":[81],"framework":[83,115],"MMCL":[84],"apply":[86,130],"contrastive":[87,119,124],"learning":[88,120,125],"three":[90],"levels,":[91],"utterance":[93,112],"level,":[94,96,113],"word":[98],"level":[99],"enable":[101],"mutually":[106],"guide":[107],"each":[108],"other.":[109],"For":[110],"our":[114,148],"implements":[116],"coarse":[117],"granularity":[118,123],"fine":[122],"simultaneously.":[126],"Besides,":[127],"also":[129],"self-distillation":[132],"method":[133],"improve":[135],"robustness":[137],"model.":[140],"Experimental":[141],"results":[142,154],"further":[144],"analysis":[145],"demonstrate":[146],"that":[147],"proposed":[149],"model":[150],"achieves":[151],"new":[152],"state-of-the-art":[153],"on":[155,167],"public":[157],"multi-intent":[158],"datasets,":[160],"obtaining":[161],"2.6":[163],"overall":[164],"accuracy":[165],"improvement":[166],"MixATIS":[168],"dataset":[169],"compared":[170],"previous":[172],"best":[173],"models.":[174]},"counts_by_year":[{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}