{"id":"https://openalex.org/W4321485482","doi":"https://doi.org/10.1145/3539597.3570479","title":"Long-Document Cross-Lingual Summarization","display_name":"Long-Document Cross-Lingual Summarization","publication_year":2023,"publication_date":"2023-02-22","ids":{"openalex":"https://openalex.org/W4321485482","doi":"https://doi.org/10.1145/3539597.3570479"},"language":"en","primary_location":{"id":"doi:10.1145/3539597.3570479","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539597.3570479","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","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/A5039515155","display_name":"Shaohui Zheng","orcid":"https://orcid.org/0000-0002-9778-9292"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaohui Zheng","raw_affiliation_strings":["Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-9778-9292","affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065529268","display_name":"Zhixu Li","orcid":"https://orcid.org/0000-0003-2355-288X"},"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":"Zhixu Li","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-2355-288X","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062115445","display_name":"Jiaan Wang","orcid":"https://orcid.org/0000-0002-2587-7648"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaan Wang","raw_affiliation_strings":["Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-2587-7648","affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055672506","display_name":"Jianfeng Qu","orcid":"https://orcid.org/0000-0002-2596-2850"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Qu","raw_affiliation_strings":["Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-2596-2850","affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100340373","display_name":"An Liu","orcid":"https://orcid.org/0000-0002-6368-576X"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"An Liu","raw_affiliation_strings":["Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-6368-576X","affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070439966","display_name":"Lei Zhao","orcid":"https://orcid.org/0000-0002-5123-9279"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhao","raw_affiliation_strings":["Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5123-9279","affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100332248","display_name":"Zhigang Chen","orcid":"https://orcid.org/0000-0001-5140-7319"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhigang Chen","raw_affiliation_strings":["Jilin Kexun Information Technology Co., Ltd., Jilin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jilin Kexun Information Technology Co., Ltd., Jilin, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1084","last_page":"1092"},"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":0.9997000098228455,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9955999851226807,"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/automatic-summarization","display_name":"Automatic summarization","score":0.9532629251480103},{"id":"https://openalex.org/keywords/cls-upper-limits","display_name":"CLs upper limits","score":0.9073182344436646},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8256947994232178},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6197364926338196},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6176362633705139},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5519595742225647},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4961293637752533},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.46621638536453247},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4532122313976288},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3432445526123047},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33261221647262573},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08087459206581116}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9532629251480103},{"id":"https://openalex.org/C190729725","wikidata":"https://www.wikidata.org/wiki/Q5012817","display_name":"CLs upper limits","level":2,"score":0.9073182344436646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8256947994232178},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6197364926338196},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6176362633705139},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5519595742225647},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4961293637752533},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.46621638536453247},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4532122313976288},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3432445526123047},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33261221647262573},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08087459206581116},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C119767625","wikidata":"https://www.wikidata.org/wiki/Q618211","display_name":"Optometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3539597.3570479","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539597.3570479","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7200000286102295,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G4866431022","display_name":null,"funder_award_id":"62072323, 62102276","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7604403865","display_name":null,"funder_award_id":"BK20210705","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1607035479","https://openalex.org/W1956340063","https://openalex.org/W1979194117","https://openalex.org/W2001642682","https://openalex.org/W2101105183","https://openalex.org/W2465299637","https://openalex.org/W2600463316","https://openalex.org/W2602331152","https://openalex.org/W2949925034","https://openalex.org/W2952138241","https://openalex.org/W2963926728","https://openalex.org/W2972111982","https://openalex.org/W3034378323","https://openalex.org/W3034999214","https://openalex.org/W3085139254","https://openalex.org/W3106445907","https://openalex.org/W3170490008","https://openalex.org/W3171639395","https://openalex.org/W3175689281","https://openalex.org/W3209950363","https://openalex.org/W4205509257","https://openalex.org/W4213228793","https://openalex.org/W4221141894","https://openalex.org/W4221151670","https://openalex.org/W4239019441","https://openalex.org/W4285126962","https://openalex.org/W6693853403"],"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/W4242223894","https://openalex.org/W4306886878","https://openalex.org/W2973759123","https://openalex.org/W1517524280"],"abstract_inverted_index":{"Cross-Lingual":[0],"Summarization":[1],"(CLS)":[2],"aims":[3],"at":[4],"generating":[5],"summaries":[6],"in":[7,14,28,110],"one":[8],"language":[9],"for":[10],"the":[11,29,89,141,144,149,163],"given":[12],"documents":[13,57,100,109],"another":[15],"language.":[16],"CLS":[17,39,81,92,129,182],"has":[18],"attracted":[19],"wide":[20],"research":[21,82],"attention":[22],"due":[23],"to":[24,75,155],"its":[25],"practical":[26],"significance":[27],"multi-lingual":[30],"world.":[31],"Though":[32],"great":[33],"contributions":[34],"have":[35],"been":[36],"made,":[37],"existing":[38],"works":[40],"typically":[41],"focus":[42],"on":[43,83,121,138],"short":[44,54],"documents,":[45,85],"such":[46,58],"as":[47,59],"news":[48],"and":[49,66,77,126,133,166,183],"guides.":[50],"Different":[51],"from":[52],"these":[53],"texts,":[55],"long":[56,84],"academic":[60],"articles":[61],"usually":[62],"discuss":[63,167],"complicated":[64],"subjects":[65],"consist":[67],"of":[68,70,108,143],"thousands":[69],"words,":[71],"making":[72],"them":[73],"non-trivial":[74],"process":[76],"summarize.":[78],"To":[79],"promote":[80],"we":[86,124,160],"construct":[87],"Perseus,":[88],"first":[90],"long-document":[91,122,181],"dataset":[93],"which":[94,147],"collects":[95],"about":[96],"94K":[97],"Chinese":[98],"scientific":[99],"paired":[101],"with":[102],"English":[103],"summaries.":[104],"The":[105],"average":[106],"length":[107],"Perseus":[111,139],"is":[112],"more":[113],"than":[114],"2000":[115],"tokens.":[116],"As":[117],"a":[118,157],"preliminary":[119],"study":[120],"CLS,":[123],"build":[125],"evaluate":[127],"various":[128],"baselines,":[130],"including":[131],"pipeline":[132],"end-to-end":[134,145],"methods.":[135,153],"Experimental":[136],"results":[137],"show":[140],"superiority":[142],"baseline,":[146],"performs":[148],"best":[150],"among":[151],"all":[152],"Furthermore,":[154],"provide":[156],"deeper":[158],"understanding,":[159],"manually":[161],"analyze":[162],"model":[164],"outputs":[165],"specific":[168],"challenges":[169],"faced":[170],"by":[171],"current":[172],"approaches.":[173],"We":[174],"hope":[175],"that":[176],"our":[177],"work":[178],"could":[179],"benchmark":[180],"benefit":[184],"future":[185],"studies.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
