{"id":"https://openalex.org/W4385570028","doi":"https://doi.org/10.18653/v1/2023.acl-long.292","title":"Distributed Marker Representation for Ambiguous Discourse Markers and Entangled Relations","display_name":"Distributed Marker Representation for Ambiguous Discourse Markers and Entangled Relations","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4385570028","doi":"https://doi.org/10.18653/v1/2023.acl-long.292"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2023.acl-long.292","doi":"https://doi.org/10.18653/v1/2023.acl-long.292","is_oa":true,"landing_page_url":"http://dx.doi.org/10.18653/v1/2023.acl-long.292","pdf_url":"https://aclanthology.org/2023.acl-long.292.pdf","source":{"id":"https://openalex.org/S4393915740","display_name":"Proceedings of the conference - Association for Computational Linguistics. Meeting","issn_l":"0736-587X","issn":["0736-587X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2023.acl-long.292.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066720399","display_name":"Dongyu Ru","orcid":"https://orcid.org/0000-0002-7380-1672","observed_orcids":["https://orcid.org/0000-0002-7380-1672"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dongyu Ru","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100750859","display_name":"Lin Qiu","orcid":"https://orcid.org/0000-0003-1236-2191","observed_orcids":["https://orcid.org/0000-0003-1236-2191","https://orcid.org/0000-0003-2331-8698"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin Qiu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044665993","display_name":"Xipeng Qiu","orcid":"https://orcid.org/0000-0001-7163-5247","observed_orcids":["https://orcid.org/0000-0001-7163-5247"]},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xipeng Qiu","raw_affiliation_strings":["School of Computer Science, Fudan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333738","display_name":"Yue Zhang","orcid":"https://orcid.org/0000-0002-6327-5023","observed_orcids":["https://orcid.org/0000-0002-6327-5023","https://orcid.org/0009-0009-2823-0151","https://orcid.org/0000-0002-5214-2268","https://orcid.org/0000-0003-3297-1082","https://orcid.org/0009-0004-1931-113X"]},"institutions":[{"id":"https://openalex.org/I3133055985","display_name":"Westlake University","ror":"https://ror.org/05hfa4n20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3133055985"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Zhang","raw_affiliation_strings":["School of Engineering, Westlake University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering, Westlake University","institution_ids":["https://openalex.org/I3133055985"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100459130","display_name":"Zheng Zhang","orcid":"https://orcid.org/0009-0008-0716-6501","observed_orcids":["https://orcid.org/0009-0008-0716-6501","https://orcid.org/0000-0002-6277-0305"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3535,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.52261226,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"5334","last_page":"5351"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.490200012922287,"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":0.490200012922287,"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":0.4636000096797943,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.015599999576807022,"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/discourse-markers","display_name":"discourse markers","score":0.9610000252723694},{"id":"https://openalex.org/keywords/implicit-discourse-relations","display_name":"implicit discourse relations","score":0.7850000262260437},{"id":"https://openalex.org/keywords/ambiguity","display_name":"ambiguity","score":0.44600000977516174},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"unsupervised learning","score":0.7559999823570251},{"id":"https://openalex.org/keywords/interpretability","display_name":"interpretability","score":0.7319999933242798}],"concepts":[{"id":"https://openalex.org/C90464235","wikidata":"https://www.wikidata.org/wiki/Q1051521","display_name":"Discourse marker","level":2,"score":0.7132003307342529},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6892263889312744},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.6744492650032043},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5970213413238525},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.5240899920463562},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.512710690498352},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4839673340320587},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4774473309516907},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47611790895462036},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.46161091327667236},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4471851587295532},{"id":"https://openalex.org/C84389358","wikidata":"https://www.wikidata.org/wiki/Q1129466","display_name":"Discourse analysis","level":2,"score":0.41452014446258545},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.08404982089996338},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/2023.acl-long.292","doi":"https://doi.org/10.18653/v1/2023.acl-long.292","is_oa":true,"landing_page_url":"http://dx.doi.org/10.18653/v1/2023.acl-long.292","pdf_url":"https://aclanthology.org/2023.acl-long.292.pdf","source":{"id":"https://openalex.org/S4393915740","display_name":"Proceedings of the conference - Association for Computational Linguistics. Meeting","issn_l":"0736-587X","issn":["0736-587X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2306.10658","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.10658","pdf_url":"https://arxiv.org/pdf/2306.10658","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2306.10658","doi":"https://doi.org/10.48550/arxiv.2306.10658","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2306.10658","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.18653/v1/2023.acl-long.292","doi":"https://doi.org/10.18653/v1/2023.acl-long.292","is_oa":true,"landing_page_url":"http://dx.doi.org/10.18653/v1/2023.acl-long.292","pdf_url":"https://aclanthology.org/2023.acl-long.292.pdf","source":{"id":"https://openalex.org/S4393915740","display_name":"Proceedings of the conference - Association for Computational Linguistics. Meeting","issn_l":"0736-587X","issn":["0736-587X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385570028.pdf","grobid_xml":"https://content.openalex.org/works/W4385570028.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W102059219","https://openalex.org/W1855867616","https://openalex.org/W2040960947","https://openalex.org/W2109462987","https://openalex.org/W2152197045","https://openalex.org/W2164567676","https://openalex.org/W2166957049","https://openalex.org/W2251826083","https://openalex.org/W2294607529","https://openalex.org/W2565756058","https://openalex.org/W2610858497","https://openalex.org/W2740924633","https://openalex.org/W2762652133","https://openalex.org/W2798240283","https://openalex.org/W2950308662","https://openalex.org/W2950375454","https://openalex.org/W2952750383","https://openalex.org/W2963020213","https://openalex.org/W2964175741","https://openalex.org/W2965362971","https://openalex.org/W2965373594","https://openalex.org/W2970474271","https://openalex.org/W2971329390","https://openalex.org/W3006216418","https://openalex.org/W3031430352","https://openalex.org/W3033962033","https://openalex.org/W3034403033","https://openalex.org/W3102009955","https://openalex.org/W4226157820","https://openalex.org/W4385573755"],"related_works":["https://openalex.org/W3028600070","https://openalex.org/W2573887004","https://openalex.org/W184034292","https://openalex.org/W2275237358","https://openalex.org/W7096320617","https://openalex.org/W6982677711","https://openalex.org/W2068136673","https://openalex.org/W2804289704","https://openalex.org/W2946579162","https://openalex.org/W7056292807"],"abstract_inverted_index":{"Discourse":[0],"analysis":[1],"is":[2,28,54],"an":[3],"important":[4],"task":[5,128],"because":[6],"it":[7],"models":[8],"intrinsic":[9],"semantic":[10],"structures":[11],"between":[12,47],"sentences":[13],"in":[14,23,107],"a":[15,51,57,73,87,135],"document.Discourse":[16],"markers":[17,31,62,93,146],"are":[18],"natural":[19],"representations":[20,97],"of":[21,119],"discourse":[22,38,65,83,89,125,145,150],"our":[24,120],"daily":[25],"language.One":[26],"challenge":[27],"that":[29,50],"the":[30,45,61,80,112,116,123],"as":[32,34],"well":[33],"pre-defined":[35],"and":[36,106,129,142,147],"human-labeled":[37],"relations":[39],"can":[40,98],"be":[41,99],"ambiguous":[42],"when":[43],"describing":[44],"semantics":[46],"sentences.We":[48],"believe":[49],"better":[52],"approach":[53],"to":[55,63,71,138],"use":[56],"contextual-dependent":[58],"distribution":[59],"over":[60],"express":[64],"information.In":[66],"this":[67],"work,":[68],"we":[69],"propose":[70],"learn":[72],"Distributed":[74],"Marker":[75],"Representation":[76],"(DMR)":[77],"by":[78],"utilizing":[79],"(potentially)":[81],"unlimited":[82],"marker":[84],"data":[85,103,113],"with":[86,94],"latent":[88],"sense,":[90],"thereby":[91],"bridging":[92],"sentence":[95],"pairs.Such":[96],"learned":[100],"automatically":[101],"from":[102],"without":[104],"supervision,":[105],"turn":[108],"provide":[109],"insights":[110],"into":[111],"itself.Experiments":[114],"show":[115],"SOTA":[117],"performance":[118],"DMR":[121],"on":[122],"implicit":[124],"relation":[126],"recognition":[127],"strong":[130],"interpretability.Our":[131],"method":[132],"also":[133],"offers":[134],"valuable":[136],"tool":[137],"understand":[139],"complex":[140],"ambiguity":[141],"entanglement":[143],"among":[144],"manually":[148],"defined":[149],"relations.":[151]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2023-08-05T00:00:00"}
