{"id":"https://openalex.org/W4414405266","doi":"https://doi.org/10.1109/iccworkshops67674.2025.11162340","title":"Investigating Distributions of Telecom Adapted Sentence Embeddings for Document Retrieval","display_name":"Investigating Distributions of Telecom Adapted Sentence Embeddings for Document Retrieval","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414405266","doi":"https://doi.org/10.1109/iccworkshops67674.2025.11162340"},"language":"en","primary_location":{"id":"doi:10.1109/iccworkshops67674.2025.11162340","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccworkshops67674.2025.11162340","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Communications Workshops (ICC Workshops)","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/A5064379712","display_name":"Sujoy Roychowdhury","orcid":null},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Sujoy Roychowdhury","raw_affiliation_strings":["Ericsson R&D,Bangalore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson R&D,Bangalore","institution_ids":["https://openalex.org/I1306339040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083371463","display_name":"Sumit Soman","orcid":"https://orcid.org/0000-0003-1926-3065"},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Sumit Soman","raw_affiliation_strings":["Ericsson R&D,Bangalore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson R&D,Bangalore","institution_ids":["https://openalex.org/I1306339040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119695099","display_name":"Ranjani Hosakere Gireesha","orcid":null},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Ranjani Hosakere Gireesha","raw_affiliation_strings":["Ericsson R&D,Bangalore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson R&D,Bangalore","institution_ids":["https://openalex.org/I1306339040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5099282400","display_name":"Vansh Chhabra","orcid":null},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Vansh Chhabra","raw_affiliation_strings":["Ericsson R&D,Bangalore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson R&D,Bangalore","institution_ids":["https://openalex.org/I1306339040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5099282401","display_name":"Neeraj Gunda","orcid":null},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Neeraj Gunda","raw_affiliation_strings":["Ericsson R&D,Bangalore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson R&D,Bangalore","institution_ids":["https://openalex.org/I1306339040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006423606","display_name":"Subhadip Bandyopadhyay","orcid":null},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Subhadip Bandyopadhyay","raw_affiliation_strings":["Ericsson R&D,Bangalore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson R&D,Bangalore","institution_ids":["https://openalex.org/I1306339040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108324304","display_name":"Sai Krishna Bala","orcid":null},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Sai Krishna Bala","raw_affiliation_strings":["Ericsson R&D,Bangalore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson R&D,Bangalore","institution_ids":["https://openalex.org/I1306339040"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11983746,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"512","last_page":"517"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9728000164031982,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.972100019454956,"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/metric","display_name":"Metric (unit)","score":0.6797999739646912},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6319000124931335},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5927000045776367},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5823000073432922},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5077000260353088},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5001000165939331},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.44670000672340393}],"concepts":[{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6797999739646912},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6718999743461609},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6319000124931335},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5927000045776367},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5823000073432922},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5080000162124634},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5077000260353088},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5001000165939331},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.44670000672340393},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.421099990606308},{"id":"https://openalex.org/C184050105","wikidata":"https://www.wikidata.org/wiki/Q273163","display_name":"Isotropy","level":2,"score":0.39730000495910645},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.38280001282691956},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.3734999895095825},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3379000127315521},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C41426520","wikidata":"https://www.wikidata.org/wiki/Q1192065","display_name":"Point estimation","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.26840001344680786},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.2590000033378601}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccworkshops67674.2025.11162340","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccworkshops67674.2025.11162340","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Communications Workshops (ICC Workshops)","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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"A":[0],"plethora":[1],"of":[2,108,137,148,195],"sentence":[3],"embedding":[4],"models":[5,40],"makes":[6],"it":[7,85],"challenging":[8],"to":[9,62],"choose":[10],"one,":[11],"especially":[12],"for":[13,30,65,68,169,177,193],"technical":[14],"domains":[15],"rich":[16],"with":[17,115,126,162,175],"specialized":[18],"vocabulary.":[19],"In":[20],"this":[21],"work,":[22],"we":[23,73,119,190],"domain":[24],"adapt":[25],"embeddings":[26,35,149,168],"using":[27],"telecom":[28],"data":[29],"question":[31],"answering.":[32],"We":[33,57,81,100,165],"evaluate":[34],"obtained":[36],"from":[37],"publicly":[38],"available":[39],"and":[41,111,129,180,198,202],"their":[42,53],"domain-adapted":[43],"variants,":[44],"on":[45,139,187],"both":[46],"point":[47],"retrieval":[48,127,140,163],"accuracies,":[49],"as":[50,52],"well":[51],"(95%)":[54],"confidence":[55,89],"intervals.":[56],"establish":[58,144],"a":[59],"systematic":[60],"method":[61],"obtain":[63],"thresholds":[64],"similarity":[66,130],"scores":[67],"different":[69],"embeddings.":[70],"As":[71],"expected,":[72],"observe":[74,83],"that":[75,84,121,145,167],"fine-tuning":[76,181],"improves":[77],"mean":[78],"bootstrapped":[79],"accuracies.":[80,141],"also":[82],"results":[86],"in":[87],"tighter":[88],"intervals,":[90],"which":[91,103],"further":[92,184],"improve":[93],"when":[94],"pre-training":[95],"is":[96,159],"preceded":[97],"by":[98,152,200],"fine-tuning.":[99],"introduce":[101],"metrics":[102,123,199],"measure":[104],"the":[105,116,146],"distributional":[106],"overlaps":[107],"top-K,":[109],"correct":[110],"random":[112],"document":[113],"similarities":[114],"question.":[117],"Further,":[118],"show":[120,166],"these":[122],"are":[124],"correlated":[125,161],"accuracy":[128],"thresholds.":[131],"Recent":[132],"literature":[133],"shows":[134],"conflicting":[135],"effects":[136],"isotropy":[138,147,156],"Our":[142],"experiments":[143],"(as":[150],"measured":[151],"two":[153],"independent":[154],"state-of-the-art":[155],"metric":[157],"definitions)":[158],"poorly":[160],"performance.":[164],"domain-specific":[170],"sentences":[171],"have":[172],"little":[173],"overlap":[174],"those":[176],"domain-agnostic":[178],"ones,":[179],"moves":[182],"them":[183],"apart.":[185],"Based":[186],"our":[188,196],"results,":[189],"provide":[191],"recommendations":[192],"use":[194],"methodology":[197],"researchers":[201],"practitioners.":[203]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}