{"id":"https://openalex.org/W4392299356","doi":"https://doi.org/10.1587/transinf.2023edp7111","title":"Hierarchical Latent Alignment for Non-Autoregressive Generation under High Compression Ratio","display_name":"Hierarchical Latent Alignment for Non-Autoregressive Generation under High Compression Ratio","publication_year":2024,"publication_date":"2024-02-29","ids":{"openalex":"https://openalex.org/W4392299356","doi":"https://doi.org/10.1587/transinf.2023edp7111"},"language":"en","primary_location":{"id":"doi:10.1587/transinf.2023edp7111","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1587/transinf.2023edp7111","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E107.D/3/E107.D_2023EDP7111/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.jstage.jst.go.jp/article/transinf/E107.D/3/E107.D_2023EDP7111/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100544586","display_name":"Wang Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang XU","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101311204","display_name":"Yongliang MA","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127487","display_name":"Vision Technology (United States)","ror":"https://ror.org/03gmxkp43","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127487"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yongliang MA","raw_affiliation_strings":["Beijing Langboat Technology Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Langboat Technology Co., Ltd","institution_ids":["https://openalex.org/I4210127487"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006323375","display_name":"Kehai Chen","orcid":"https://orcid.org/0000-0002-4346-7618"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kehai CHEN","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100701574","display_name":"Ming Zhou","orcid":"https://orcid.org/0000-0002-5701-1996"},"institutions":[{"id":"https://openalex.org/I4210127487","display_name":"Vision Technology (United States)","ror":"https://ror.org/03gmxkp43","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127487"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming ZHOU","raw_affiliation_strings":["Beijing Langboat Technology Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Langboat Technology Co., Ltd","institution_ids":["https://openalex.org/I4210127487"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108053327","display_name":"Muyun Yang","orcid":"https://orcid.org/0000-0002-5940-0266"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Muyun YANG","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101661008","display_name":"Tiejun Zhao","orcid":"https://orcid.org/0000-0003-4659-4935"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiejun ZHAO","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01612469,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"E107.D","issue":"3","first_page":"411","last_page":"419"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","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/T10181","display_name":"Natural Language Processing Techniques","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/T10028","display_name":"Topic Modeling","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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9939000010490417,"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":0.8894858360290527},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.8057198524475098},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6892576217651367},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5355406403541565},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5014336109161377},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.46695810556411743},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4485350251197815},{"id":"https://openalex.org/keywords/compression-ratio","display_name":"Compression ratio","score":0.43644821643829346},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.43618834018707275},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.43414053320884705},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.4115646481513977},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.384330689907074},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35570192337036133},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20429477095603943}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8894858360290527},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8057198524475098},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6892576217651367},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5355406403541565},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5014336109161377},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.46695810556411743},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4485350251197815},{"id":"https://openalex.org/C25797200","wikidata":"https://www.wikidata.org/wiki/Q828137","display_name":"Compression ratio","level":3,"score":0.43644821643829346},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.43618834018707275},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.43414053320884705},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.4115646481513977},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.384330689907074},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35570192337036133},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20429477095603943},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.0},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C511840579","wikidata":"https://www.wikidata.org/wiki/Q12757","display_name":"Internal combustion engine","level":2,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transinf.2023edp7111","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1587/transinf.2023edp7111","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E107.D/3/E107.D_2023EDP7111/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transinf.2023edp7111","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1587/transinf.2023edp7111","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E107.D/3/E107.D_2023EDP7111/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392299356.pdf"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1544827683","https://openalex.org/W1821462560","https://openalex.org/W1978613528","https://openalex.org/W2103339462","https://openalex.org/W2127141656","https://openalex.org/W2750941728","https://openalex.org/W2767206889","https://openalex.org/W2888482885","https://openalex.org/W2892213699","https://openalex.org/W2933138175","https://openalex.org/W2952215948","https://openalex.org/W2963929190","https://openalex.org/W2964061924","https://openalex.org/W2981648103","https://openalex.org/W2986772082","https://openalex.org/W2988975212","https://openalex.org/W2996987694","https://openalex.org/W3015162217","https://openalex.org/W3034539042","https://openalex.org/W3035050380","https://openalex.org/W3100053428","https://openalex.org/W3100753857","https://openalex.org/W3126267552","https://openalex.org/W3154504973","https://openalex.org/W3166462744","https://openalex.org/W3170083118","https://openalex.org/W3175665465","https://openalex.org/W3206889547","https://openalex.org/W4280567072","https://openalex.org/W4281690172","https://openalex.org/W4281806233","https://openalex.org/W4285110265","https://openalex.org/W4304699956","https://openalex.org/W4304700921","https://openalex.org/W4377079846","https://openalex.org/W4385573336"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W4389760904","https://openalex.org/W2150160875","https://openalex.org/W4284703357","https://openalex.org/W2949968076","https://openalex.org/W2935811960","https://openalex.org/W2969407538"],"abstract_inverted_index":{"Non-autoregressive":[0],"generation":[1],"has":[2],"attracted":[3],"more":[4,6],"and":[5,30,40,64,77,99,101,126],"attention":[7],"due":[8],"to":[9,22],"its":[10],"fast":[11],"decoding":[12],"speed.":[13],"Latent":[14,80],"alignment":[15,89,105],"objectives,":[16],"such":[17],"as":[18],"CTC,":[19],"are":[20],"designed":[21],"capture":[23],"the":[24,28,62,94,97,114],"monotonic":[25],"alignments":[26],"between":[27,61],"predicted":[29],"output":[31,65],"tokens,":[32],"which":[33],"have":[34],"been":[35],"used":[36,123],"for":[37],"machine":[38],"translation":[39],"sentence":[41],"summarization.":[42],"However,":[43],"our":[44,117,132],"preliminary":[45],"experiments":[46],"revealed":[47],"that":[48,131],"CTC":[49,107],"performs":[50],"poorly":[51],"on":[52,109,120],"document":[53],"abstractive":[54],"summarization,":[55],"where":[56],"a":[57,74,87],"high":[58,142],"compression":[59,143],"ratio":[60],"input":[63,98],"is":[66,86],"involved.":[67],"To":[68],"address":[69],"this":[70],"issue,":[71],"we":[72,91],"conduct":[73],"theoretical":[75],"analysis":[76],"propose":[78],"Hierarchical":[79],"Alignment":[81],"(HLA).":[82],"The":[83,128],"basic":[84],"idea":[85],"two-step":[88],"process:":[90],"first":[92],"align":[93],"sentences":[95],"in":[96],"output,":[100],"subsequently":[102],"derive":[103],"token-level":[104],"using":[106],"based":[108],"aligned":[110],"sentences.":[111],"We":[112],"evaluate":[113],"effectiveness":[115],"of":[116],"proposed":[118,133],"approach":[119],"two":[121],"widely":[122],"datasets":[124],"XSUM":[125],"CNNDM.":[127],"results":[129],"indicate":[130],"method":[134],"exhibits":[135],"remarkable":[136],"scalability":[137],"even":[138],"when":[139],"dealing":[140],"with":[141],"ratios.":[144]},"counts_by_year":[],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}
