乐胖代购免代理版

{"id":"https://openalex.org/W4385573208","doi":"https://doi.org/10.18653/v1/2022.emnlp-main.338","title":"Contrastive Learning enhanced Author-Style Headline Generation","display_name":"Contrastive Learning enhanced Author-Style Headline Generation","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4385573208","doi":"https://doi.org/10.18653/v1/2022.emnlp-main.338"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.emnlp-main.338","pdf_url":"https://aclanthology.org/2022.emnlp-main.338.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2022.emnlp-main.338.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100387661","display_name":"Hui Liu","orcid":"https://orcid.org/0000-0003-2992-5018"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Liu","raw_affiliation_strings":["Platform and Content Group, Tencent"],"affiliations":[{"raw_affiliation_string":"Platform and Content Group, Tencent","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038898235","display_name":"Weidong Guo","orcid":"https://orcid.org/0000-0003-0299-6393"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weidong Guo","raw_affiliation_strings":["Platform and Content Group, Tencent"],"affiliations":[{"raw_affiliation_string":"Platform and Content Group, Tencent","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040565656","display_name":"Yige Chen","orcid":"https://orcid.org/0000-0002-0430-0057"},"institutions":[{"id":"https://openalex.org/I146620803","display_name":"Wenzhou University","ror":"https://ror.org/020hxh324","country_code":"CN","type":"education","lineage":["https://openalex.org/I146620803"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yige Chen","raw_affiliation_strings":["College of Computer Science and Artificial Intelligence, Wenzhou University"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Artificial Intelligence, Wenzhou University","institution_ids":["https://openalex.org/I146620803"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100341802","display_name":"Xiang\u2010Yang Li","orcid":"https://orcid.org/0000-0002-6070-6625"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyang Li","raw_affiliation_strings":["Platform and Content Group, Tencent"],"affiliations":[{"raw_affiliation_string":"Platform and Content Group, Tencent","institution_ids":["https://openalex.org/I2250653659"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.321,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":2,"citation_normalized_percentile":{"value":0.658299,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":70,"max":76},"biblio":{"volume":null,"issue":null,"first_page":"5063","last_page":"5072"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9988,"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":0.9988,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9984,"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"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9967,"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/headline","display_name":"Headline","score":0.9949086}],"concepts":[{"id":"https://openalex.org/C2778689934","wikidata":"https://www.wikidata.org/wiki/Q1313396","display_name":"Headline","level":2,"score":0.9949086},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.77820945},{"id":"https://openalex.org/C2776445246","wikidata":"https://www.wikidata.org/wiki/Q1792644","display_name":"Style (visual arts)","level":2,"score":0.61204565},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5995991},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5894438},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4701246},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.43053123},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.41083592},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.08294001},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.074846804},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.emnlp-main.338","pdf_url":"https://aclanthology.org/2022.emnlp-main.338.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2211.03305","pdf_url":"https://arxiv.org/pdf/2211.03305","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.emnlp-main.338","pdf_url":"https://aclanthology.org/2022.emnlp-main.338.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality education","score":0.89}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":22,"referenced_works":["https://openalex.org/W2133564696","https://openalex.org/W2154652894","https://openalex.org/W2606974598","https://openalex.org/W2741438349","https://openalex.org/W2896375520","https://openalex.org/W2896457183","https://openalex.org/W2914442349","https://openalex.org/W2914949666","https://openalex.org/W2952335829","https://openalex.org/W2952468927","https://openalex.org/W2970634364","https://openalex.org/W3005680577","https://openalex.org/W3035068386","https://openalex.org/W3098672388","https://openalex.org/W3100955355","https://openalex.org/W3128699722","https://openalex.org/W3173210704","https://openalex.org/W3176778415","https://openalex.org/W4286963014","https://openalex.org/W4288089799","https://openalex.org/W4293569541","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W906669285","https://openalex.org/W85886512","https://openalex.org/W4285135530","https://openalex.org/W3173716828","https://openalex.org/W2515595154","https://openalex.org/W2380567098","https://openalex.org/W2035489689","https://openalex.org/W1586468330","https://openalex.org/W1553197492","https://openalex.org/W1514610457"],"abstract_inverted_index":{"Headline":[0,65],"generation":[1,87,188],"is":[2],"a":[3,11,53,111,140],"task":[4,145],"of":[5,44,73,88,103,134,149,180],"generating":[6],"an":[7],"appropriate":[8,115],"headline":[9,86,112,187],"for":[10,19,116,146],"given":[12],"article,":[13,118],"which":[14,67],"can":[15,68,98,184,203],"be":[16],"further":[17,138,204],"used":[18],"machine-aided":[20],"writing":[21,42],"or":[22],"enhancing":[23],"the":[24,31,35,41,70,74,77,81,85,100,104,117,123,131,135,147,159,166,169,172,181,186,192,197,206],"click-through":[25],"ratio.":[26],"Current":[27],"works":[28],"only":[29,114],"use":[30,69,158],"article":[32],"itself":[33],"in":[34,80],"generation,":[36],"but":[37,119],"have":[38],"not":[39,113],"taken":[40],"style":[43,199],"headlines":[45,72,94,179],"into":[46,95,106],"consideration.":[47],"In":[48,126],"this":[49],"paper,":[50],"we":[51,97,137,153],"propose":[52,154],"novel":[54],"Seq2Seq":[55],"model":[56],"called":[57],"CLH3G":[58],"(Contrastive":[59],"Learning":[60],"enhanced":[61],"Historical":[62],"Headlines":[63],"based":[64,143],"Generation)":[66],"historical":[71,93,178],"articles":[75],"that":[76,177],"author":[78,105],"wrote":[79],"past":[82],"to":[83,128,157,163],"improve":[84,185],"current":[89],"articles.":[90],"By":[91],"taking":[92],"account,":[96],"integrate":[99],"stylistic":[101,132,161],"features":[102,133,162,200],"our":[107,150],"model,":[108],"and":[109,168,190,196],"generate":[110],"also":[120],"consistent":[121],"with":[122],"author\u2019s":[124],"style.":[125],"order":[127],"efficiently":[129],"learn":[130],"author,":[136],"introduce":[139],"contrastive":[141,193],"learning":[142,194],"auxiliary":[144],"encoder":[148],"model.":[151],"Besides,":[152],"two":[155,198],"methods":[156,202],"learned":[160],"guide":[164],"both":[165,191],"pointer":[167],"decoder":[170],"during":[171],"generation.":[173],"Experimental":[174],"results":[175],"show":[176],"same":[182],"user":[183],"significantly,":[189],"module":[195],"fusion":[201],"boost":[205],"performance.":[207]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4385573208","counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2024-12-13T21:58:47.245054","created_date":"2023-08-05"}