{"id":"https://openalex.org/W2963411289","doi":"https://doi.org/10.18653/v1/p18-1101","title":"Unsupervised Discrete Sentence Representation Learning for Interpretable Neural Dialog Generation","display_name":"Unsupervised Discrete Sentence Representation Learning for Interpretable Neural Dialog Generation","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2963411289","doi":"https://doi.org/10.18653/v1/p18-1101","mag":"2963411289"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p18-1101","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1101","pdf_url":"https://www.aclweb.org/anthology/P18-1101.pdf","source":null,"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 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P18-1101.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114246802","display_name":"Tiancheng Zhao","orcid":"https://orcid.org/0000-0002-7443-0666"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tiancheng Zhao","raw_affiliation_strings":["Language Technologies Institute Carnegie Mellon University Pittsburgh, Pennsylvania, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Language Technologies Institute Carnegie Mellon University Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043150565","display_name":"Kyusong Lee","orcid":"https://orcid.org/0009-0003-8113-4667"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kyusong Lee","raw_affiliation_strings":["Language Technologies Institute Carnegie Mellon University Pittsburgh, Pennsylvania, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Language Technologies Institute Carnegie Mellon University Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077285164","display_name":"Maxine Esk\u00e9nazi","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maxine Eskenazi","raw_affiliation_strings":["Language Technologies Institute Carnegie Mellon University Pittsburgh, Pennsylvania, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Language Technologies Institute Carnegie Mellon University Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":17.2335,"has_fulltext":true,"cited_by_count":137,"citation_normalized_percentile":{"value":0.99248536,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1098","last_page":"1107"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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":0.9994000196456909,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9975000023841858,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/dialog-box","display_name":"Dialog box","score":0.8853938579559326},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8228565454483032},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7080982327461243},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.6645464897155762},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6577213406562805},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6474569439888},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6342754364013672},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5960694551467896},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5763675570487976},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.483793705701828},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3687790334224701},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08504277467727661}],"concepts":[{"id":"https://openalex.org/C173853756","wikidata":"https://www.wikidata.org/wiki/Q86915","display_name":"Dialog box","level":2,"score":0.8853938579559326},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8228565454483032},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7080982327461243},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.6645464897155762},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6577213406562805},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6474569439888},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6342754364013672},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5960694551467896},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5763675570487976},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.483793705701828},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3687790334224701},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08504277467727661},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p18-1101","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1101","pdf_url":"https://www.aclweb.org/anthology/P18-1101.pdf","source":null,"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 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p18-1101","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1101","pdf_url":"https://www.aclweb.org/anthology/P18-1101.pdf","source":null,"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 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963411289.pdf","grobid_xml":"https://content.openalex.org/works/W2963411289.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W179875071","https://openalex.org/W1486649854","https://openalex.org/W1522301498","https://openalex.org/W1576632330","https://openalex.org/W1591801644","https://openalex.org/W1632114991","https://openalex.org/W1778387566","https://openalex.org/W1880262756","https://openalex.org/W1924770834","https://openalex.org/W1959608418","https://openalex.org/W2101308260","https://openalex.org/W2128970689","https://openalex.org/W2138615112","https://openalex.org/W2148256745","https://openalex.org/W2157331557","https://openalex.org/W2162833336","https://openalex.org/W2173681125","https://openalex.org/W2346887341","https://openalex.org/W2438667436","https://openalex.org/W2470875822","https://openalex.org/W2547875792","https://openalex.org/W2548228487","https://openalex.org/W2560512785","https://openalex.org/W2593696076","https://openalex.org/W2622563070","https://openalex.org/W2624872001","https://openalex.org/W2761590056","https://openalex.org/W2882319491","https://openalex.org/W2950037544","https://openalex.org/W2952165242","https://openalex.org/W2953046278","https://openalex.org/W2962717182","https://openalex.org/W2963134326","https://openalex.org/W2963223306","https://openalex.org/W2963491014","https://openalex.org/W2963544536","https://openalex.org/W2963645026","https://openalex.org/W2963773425","https://openalex.org/W2963790827","https://openalex.org/W2963799213","https://openalex.org/W2963804993","https://openalex.org/W2964121744","https://openalex.org/W2964222296","https://openalex.org/W2964352131","https://openalex.org/W3022187094","https://openalex.org/W4293568373","https://openalex.org/W4320013820"],"related_works":["https://openalex.org/W2098987383","https://openalex.org/W2417260800","https://openalex.org/W1596203174","https://openalex.org/W2117933979","https://openalex.org/W2283130723","https://openalex.org/W103938586","https://openalex.org/W2104718772","https://openalex.org/W4233992201","https://openalex.org/W2292950558","https://openalex.org/W2368721880"],"abstract_inverted_index":{"The":[0],"encoder-decoder":[1,106],"dialog":[2,14,57,98],"model":[3],"is":[4,21],"one":[5],"of":[6],"the":[7],"most":[8],"prominent":[9],"methods":[10,92],"used":[11],"to":[12,100],"build":[13],"systems":[15],"in":[16,30],"complex":[17],"domains.":[18],"Yet":[19],"it":[20,24],"limited":[22],"because":[23],"cannot":[25],"output":[26],"interpretable":[27,60,82,109],"actions":[28],"as":[29],"traditional":[31],"systems,":[32],"which":[33],"hinders":[34],"humans":[35],"from":[36],"understanding":[37],"its":[38],"generation":[39],"process.":[40],"We":[41],"present":[42,69],"an":[43],"unsupervised":[44],"discrete":[45],"sentence":[46],"representation":[47],"learning":[48],"method":[49],"that":[50,76],"can":[51,80],"integrate":[52],"with":[53,108],"any":[54],"existing":[55],"encoderdecoder":[56],"models":[58,107],"for":[59],"response":[61],"generation.":[62,110],"Building":[63],"upon":[64],"variational":[65],"autoencoders":[66],"(VAEs),":[67],"we":[68],"two":[70],"novel":[71],"models,":[72],"DI-VAE":[73],"and":[74,79,104],"DI-VST":[75],"improve":[77],"VAEs":[78],"discover":[81,101],"semantics":[83],"via":[84],"either":[85],"auto":[86],"encoding":[87],"or":[88],"context":[89],"predicting.":[90],"Our":[91],"have":[93],"been":[94],"validated":[95],"on":[96],"real-world":[97],"datasets":[99],"semantic":[102],"representations":[103],"enhance":[105],"1":[111]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":38},{"year":2019,"cited_by_count":40},{"year":2018,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
