{"id":"https://openalex.org/W4280581589","doi":"https://doi.org/10.24963/ijcai.2022/593","title":"Abstract Rule Learning for Paraphrase Generation","display_name":"Abstract Rule Learning for Paraphrase Generation","publication_year":2022,"publication_date":"2022-07-01","ids":{"openalex":"https://openalex.org/W4280581589","doi":"https://doi.org/10.24963/ijcai.2022/593"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2022/593","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/593","pdf_url":"https://www.ijcai.org/proceedings/2022/0593.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-abstract","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2022/0593.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037847115","display_name":"Xianggen Liu","orcid":"https://orcid.org/0000-0001-6368-2043"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianggen Liu","raw_affiliation_strings":["Sichuan University","College of Computer Science, Sichuan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University","institution_ids":["https://openalex.org/I24185976"]},{"raw_affiliation_string":"College of Computer Science, Sichuan University","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039239180","display_name":"Wenqiang Lei","orcid":"https://orcid.org/0000-0001-6540-0601"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqiang Lei","raw_affiliation_strings":["Sichuan University","College of Computer Science, Sichuan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University","institution_ids":["https://openalex.org/I24185976"]},{"raw_affiliation_string":"College of Computer Science, Sichuan University","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073535763","display_name":"Jiancheng Lv","orcid":"https://orcid.org/0000-0001-6551-3884"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiancheng Lv","raw_affiliation_strings":["Sichuan University","College of Computer Science, Sichuan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University","institution_ids":["https://openalex.org/I24185976"]},{"raw_affiliation_string":"College of Computer Science, Sichuan University","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102918720","display_name":"Jizhe Zhou","orcid":"https://orcid.org/0000-0001-9093-7697"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jizhe Zhou","raw_affiliation_strings":["Sichuan University","College of Computer Science, Sichuan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University","institution_ids":["https://openalex.org/I24185976"]},{"raw_affiliation_string":"College of Computer Science, Sichuan University","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4273","last_page":"4279"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9998000264167786,"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":0.9993000030517578,"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/paraphrase","display_name":"Paraphrase","score":0.9557536244392395},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7710579037666321},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7304692268371582},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7067143321037292},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5782523155212402},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5592736005783081},{"id":"https://openalex.org/keywords/ruler","display_name":"Ruler","score":0.5565763115882874},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5216969847679138},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4799402356147766},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.4739021360874176},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40387219190597534},{"id":"https://openalex.org/keywords/epistemology","display_name":"Epistemology","score":0.07729744911193848}],"concepts":[{"id":"https://openalex.org/C2780922921","wikidata":"https://www.wikidata.org/wiki/Q255189","display_name":"Paraphrase","level":2,"score":0.9557536244392395},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7710579037666321},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7304692268371582},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7067143321037292},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5782523155212402},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5592736005783081},{"id":"https://openalex.org/C165743212","wikidata":"https://www.wikidata.org/wiki/Q104555","display_name":"Ruler","level":2,"score":0.5565763115882874},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5216969847679138},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4799402356147766},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4739021360874176},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40387219190597534},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.07729744911193848},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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":1,"locations":[{"id":"doi:10.24963/ijcai.2022/593","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/593","pdf_url":"https://www.ijcai.org/proceedings/2022/0593.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2022/593","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/593","pdf_url":"https://www.ijcai.org/proceedings/2022/0593.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7400000095367432}],"awards":[{"id":"https://openalex.org/G6846722749","display_name":null,"funder_award_id":"61836006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4280581589.pdf"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W174630521","https://openalex.org/W1979539191","https://openalex.org/W2103081392","https://openalex.org/W2118119027","https://openalex.org/W2119717200","https://openalex.org/W2126034021","https://openalex.org/W2131726681","https://openalex.org/W2311110368","https://openalex.org/W2531908596","https://openalex.org/W2752796333","https://openalex.org/W2755124548","https://openalex.org/W2898823228","https://openalex.org/W2945232141","https://openalex.org/W2949832505","https://openalex.org/W2951718443","https://openalex.org/W2953369829","https://openalex.org/W2963127467","https://openalex.org/W2963687836","https://openalex.org/W2963799213","https://openalex.org/W2964202145","https://openalex.org/W2964212550","https://openalex.org/W2970419266","https://openalex.org/W2972136110","https://openalex.org/W3017342174","https://openalex.org/W3022065131","https://openalex.org/W3034531294","https://openalex.org/W3034898894","https://openalex.org/W3035368872","https://openalex.org/W3177034458","https://openalex.org/W3196732196","https://openalex.org/W4287906183","https://openalex.org/W4385245566","https://openalex.org/W6678475298","https://openalex.org/W6755811877","https://openalex.org/W6764827665","https://openalex.org/W6796102422","https://openalex.org/W6803771590","https://openalex.org/W6834709193","https://openalex.org/W6864014924"],"related_works":["https://openalex.org/W191017350","https://openalex.org/W4206666510","https://openalex.org/W2018298289","https://openalex.org/W2782520308","https://openalex.org/W2905433371","https://openalex.org/W2314732661","https://openalex.org/W2375237205","https://openalex.org/W3175194702","https://openalex.org/W2483832295","https://openalex.org/W4321512656"],"abstract_inverted_index":{"In":[0,58,97],"early":[1],"years,":[2],"paraphrase":[3,91,148],"generation":[4,92],"typically":[5],"adopts":[6],"rule-based":[7],"methods,":[8],"which":[9],"are":[10,45,49],"interpretable":[11],"and":[12,48,152],"able":[13],"to":[14,18,25,51,55,82,106,110,121],"make":[15,52],"global":[16],"transformations":[17],"the":[19,41,56,90,108,114,126,130,137],"original":[20],"sentence.":[21],"But":[22],"they":[23],"struggle":[24],"produce":[26],"fluent":[27],"paraphrases.":[28,39],"Recently,":[29],"deep":[30],"neural":[31,43,95,119],"networks":[32,120],"have":[33],"shown":[34],"impressive":[35],"performances":[36],"in":[37,145],"generating":[38],"However,":[40],"current":[42],"models":[44],"black":[46],"boxes":[47],"prone":[50],"local":[53],"modifications":[54],"inputs.":[57],"this":[59],"work,":[60],"we":[61,99,117],"combine":[62],"these":[63],"two":[64],"approaches":[65],"into":[66],"RULER,":[67,98],"a":[68,102],"novel":[69],"approach":[70],"that":[71,87],"performs":[72],"abstract":[73],"rule":[74,103],"learning":[75],"for":[76],"paraphrasing.":[77,115],"The":[78],"key":[79],"idea":[80],"is":[81],"explicitly":[83],"learn":[84],"generalizable":[85],"rules":[86,112],"could":[88],"enhance":[89],"process":[93],"of":[94,139,147],"networks.":[96],"first":[100],"propose":[101],"generalizability":[104],"metric":[105],"guide":[107],"model":[109],"generate":[111,122],"underlying":[113],"Then,":[116],"leverage":[118],"paraphrases":[123],"by":[124,129],"refining":[125],"sentences":[127],"transformed":[128],"learned":[131],"rules.":[132],"Extensive":[133],"experimental":[134],"results":[135],"demonstrate":[136],"superiority":[138],"RULER":[140],"over":[141],"previous":[142],"state-of-the-art":[143],"methods":[144],"terms":[146],"quality,":[149],"generalization":[150],"ability":[151],"interpretability.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":4}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}
