{"id":"https://openalex.org/W4415536239","doi":"https://doi.org/10.1145/3746027.3755835","title":"TeleAntiFraud-28k: An Audio-Text Slow-Thinking Dataset for Telecom Fraud Detection","display_name":"TeleAntiFraud-28k: An Audio-Text Slow-Thinking Dataset for Telecom Fraud Detection","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415536239","doi":"https://doi.org/10.1145/3746027.3755835"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755835","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755835","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","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/A5102704398","display_name":"Zhiming Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiming Ma","raw_affiliation_strings":["China Mobile Internet Company Limited, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0004-5955-7978","affiliations":[{"raw_affiliation_string":"China Mobile Internet Company Limited, Guangzhou, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Peidong Wang","orcid":"https://orcid.org/0009-0008-5015-1065"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peidong Wang","raw_affiliation_strings":["Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0009-0008-5015-1065","affiliations":[{"raw_affiliation_string":"Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Minhua Huang","orcid":"https://orcid.org/0009-0001-3325-6032"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minhua Huang","raw_affiliation_strings":["China Mobile Internet Company Ltd., Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0001-3325-6032","affiliations":[{"raw_affiliation_string":"China Mobile Internet Company Ltd., Guangzhou, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064884764","display_name":"Jinpeng Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinpeng Wang","raw_affiliation_strings":["China Mobile Internet Company Ltd., Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0001-3501-2760","affiliations":[{"raw_affiliation_string":"China Mobile Internet Company Ltd., Guangzhou, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037067048","display_name":"Kai Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Wu","raw_affiliation_strings":["China Mobile Internet Company Ltd., Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0002-3749-6268","affiliations":[{"raw_affiliation_string":"China Mobile Internet Company Ltd., Guangzhou, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiangzhao Lv","orcid":"https://orcid.org/0009-0008-6989-3747"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangzhao Lv","raw_affiliation_strings":["China Mobile Internet Company Ltd., Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0008-6989-3747","affiliations":[{"raw_affiliation_string":"China Mobile Internet Company Ltd., Guangzhou, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080630443","display_name":"Ya-Ju Pang","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yachun Pang","raw_affiliation_strings":["China Mobile Internet Company Ltd., Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0007-3939-7251","affiliations":[{"raw_affiliation_string":"China Mobile Internet Company Ltd., Guangzhou, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yin Yang","orcid":"https://orcid.org/0009-0004-9655-7432"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yin Yang","raw_affiliation_strings":["China Mobile Internet Company Ltd., Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0004-9655-7432","affiliations":[{"raw_affiliation_string":"China Mobile Internet Company Ltd., Guangzhou, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wenjie Tang","orcid":"https://orcid.org/0009-0004-0625-659X"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjie Tang","raw_affiliation_strings":["China Mobile Internet Company Ltd., Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0004-0625-659X","affiliations":[{"raw_affiliation_string":"China Mobile Internet Company Ltd., Guangzhou, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yuchen Kang","orcid":"https://orcid.org/0009-0007-6390-9050"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuchen Kang","raw_affiliation_strings":["China Mobile Internet Company Ltd., Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0007-6390-9050","affiliations":[{"raw_affiliation_string":"China Mobile Internet Company Ltd., Guangzhou, China","institution_ids":["https://openalex.org/I180662265"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":10,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.1531,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.94768469,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5853","last_page":"5862"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9635000228881836,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11309","display_name":"Music and Audio Processing","score":0.9635000228881836,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.9491000175476074,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.942300021648407,"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/construct","display_name":"Construct (python library)","score":0.675000011920929},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6129999756813049},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5759000182151794},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5601000189781189},{"id":"https://openalex.org/keywords/conversation","display_name":"Conversation","score":0.535099983215332},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4456000030040741},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.34880000352859497},{"id":"https://openalex.org/keywords/duration","display_name":"Duration (music)","score":0.3474999964237213},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.3458999991416931}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8219000101089478},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.675000011920929},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6129999756813049},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5759000182151794},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5601000189781189},{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.535099983215332},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4456000030040741},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35670000314712524},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3481000065803528},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.3474999964237213},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3458999991416931},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33739998936653137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33469998836517334},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2791999876499176},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C142603982","wikidata":"https://www.wikidata.org/wiki/Q5021615","display_name":"Call duration","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C2778403875","wikidata":"https://www.wikidata.org/wiki/Q20312394","display_name":"Adversarial machine learning","level":3,"score":0.25679999589920044},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2531000077724457},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755835","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755835","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W3190583569","https://openalex.org/W4406461186"],"related_works":[],"abstract_inverted_index":{"The":[0,112,138,230],"detection":[1,181],"of":[2,12,126,170,232],"telecom":[3,42,179],"fraud":[4,43,99,106,136,147,149,180],"faces":[5],"significant":[6],"challenges":[7,223],"due":[8],"to":[9,88,166,205],"the":[10,32,109,195,201],"lack":[11],"high-quality":[13],"multimodal":[14,217],"training":[15,197],"data":[16,202,225],"that":[17],"integrates":[18],"audio":[19,124],"signals":[20],"with":[21,121,132],"reasoning-oriented":[22],"textual":[23],"analysis.":[24,44],"To":[25],"address":[26],"this":[27,233],"gap,":[28],"we":[29,153],"present":[30],"TeleAntiFraud-28k,":[31,165],"first":[33],"open-source":[34],"audio-text":[35,119],"slow-thinking":[36],"dataset":[37,46,114,139,208],"specifically":[38],"designed":[39],"for":[40,135,216],"automated":[41],"Our":[45],"is":[47,140,235],"constructed":[48],"through":[49,70,101],"three":[50,143],"strategies:":[51],"(1)":[52],"Privacy-preserved":[53],"text-truth":[54],"sample":[55],"generation":[56],"using":[57],"automatically":[58],"speech":[59],"recognition-transcribed":[60],"call":[61],"recordings":[62],"(with":[63],"anonymized":[64],"original":[65],"audio),":[66],"ensuring":[67],"real-world":[68],"consistency":[69],"text-to-speech":[71],"model":[72,80,171,189],"regeneration;":[73],"(2)":[74],"Semantic":[75],"enhancement":[76],"via":[77],"large":[78],"language":[79],"based":[81,190],"self-instruction":[82],"sampling":[83],"on":[84,178,191,194],"authentic":[85],"ASR":[86],"outputs":[87],"expand":[89],"scenario":[90,145,228],"coverage;":[91],"(3)":[92],"Multi-agent":[93],"adversarial":[94],"synthesis,":[95],"which":[96],"simulates":[97],"emerging":[98],"tactics":[100],"predefined":[102],"communication":[103],"scenarios":[104],"and":[105,175,227],"typologies,":[107],"enriches":[108],"conversation":[110],"samples.":[111],"generated":[113],"contains":[115],"28,511":[116],"rigorously":[117],"processed":[118],"pairs":[120],"a":[122,156,186,213],"total":[123],"duration":[125],"more":[127],"than":[128],"307":[129],"hours,":[130],"complete":[131],"detailed":[133],"annotations":[134],"reasoning.":[137],"divided":[141],"into":[142],"tasks:":[144],"classification,":[146],"detection,":[148],"type":[150],"classification.":[151],"Furthermore,":[152],"construct":[154],"TeleAntiFraud-Bench,":[155],"standardized":[157],"evaluation":[158],"benchmark":[159],"comprising":[160],"proportionally":[161],"sampled":[162],"instances":[163],"from":[164],"facilitate":[167],"systematic":[168],"testing":[169],"performance,":[172],"reasoning":[173],"capabilities,":[174],"thought":[176],"processes":[177],"tasks.":[182],"We":[183],"also":[184],"contribute":[185],"supervised":[187],"fine-tuning":[188],"Qwen2-Audio,":[192],"trained":[193],"TeleAntiFraud-28k":[196],"set,":[198],"while":[199,220],"open-sourcing":[200],"processing":[203],"framework":[204,215],"enable":[206],"community-driven":[207],"expansion.":[209],"This":[210],"work":[211],"establishes":[212],"foundational":[214],"anti-fraud":[218],"research":[219],"addressing":[221],"critical":[222],"in":[224],"privacy":[226],"diversity.":[229],"code":[231],"paper":[234],"publicly":[236],"available":[237],"at":[238],"https://github.com/JimmyMa99/TeleAntiFraud.":[239]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-17T08:01:34.144755","created_date":"2025-10-25T00:00:00"}
