{"id":"https://openalex.org/W4402351321","doi":"https://doi.org/10.1109/ijcnn60899.2024.10649960","title":"Reasoning Knowledge Transfer for Logical Table-to-Text Generation","display_name":"Reasoning Knowledge Transfer for Logical Table-to-Text Generation","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402351321","doi":"https://doi.org/10.1109/ijcnn60899.2024.10649960"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10649960","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10649960","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","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/A5037855872","display_name":"Baoqiang Liu","orcid":"https://orcid.org/0000-0002-1239-8904"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Baoqiang Liu","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,ShenYang,China"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,ShenYang,China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5098769886","display_name":"Yu Bai","orcid":"https://orcid.org/0009-0009-1259-9106"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Bai","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,ShenYang,China"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,ShenYang,China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067279159","display_name":"Fang Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fang Cai","raw_affiliation_strings":["Stanford University,Department of Statistics,Stanford,USA"],"affiliations":[{"raw_affiliation_string":"Stanford University,Department of Statistics,Stanford,USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112114191","display_name":"Shuang Xue","orcid":null},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Xue","raw_affiliation_strings":["Shenyang Aerospace University,School of Foreign Language,ShenYang,China"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Foreign Language,ShenYang,China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101473298","display_name":"Na Ye","orcid":"https://orcid.org/0000-0001-5985-2281"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Na Ye","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,ShenYang,China"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,ShenYang,China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075687331","display_name":"Xinyuan Ye","orcid":"https://orcid.org/0009-0001-2046-7711"},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"XinYuan Ye","raw_affiliation_strings":["Computing and Cybernetics The Australian National University,College of Engineering,Canberra,Australia"],"affiliations":[{"raw_affiliation_string":"Computing and Cybernetics The Australian National University,College of Engineering,Canberra,Australia","institution_ids":["https://openalex.org/I118347636"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5037855872"],"corresponding_institution_ids":["https://openalex.org/I125904092"],"apc_list":null,"apc_paid":null,"fwci":0.3637,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.66462266,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9990000128746033,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9990000128746033,"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":0.9977999925613403,"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":0.9879000186920166,"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":0.7432740926742554},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.6100159287452698},{"id":"https://openalex.org/keywords/truth-table","display_name":"Truth table","score":0.43682074546813965},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34863364696502686},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.34287896752357483},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.11416637897491455},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.11176404356956482}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7432740926742554},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.6100159287452698},{"id":"https://openalex.org/C56949724","wikidata":"https://www.wikidata.org/wiki/Q219079","display_name":"Truth table","level":2,"score":0.43682074546813965},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34863364696502686},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34287896752357483},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11416637897491455},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.11176404356956482}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10649960","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10649960","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2101105183","https://openalex.org/W2137802981","https://openalex.org/W2739046565","https://openalex.org/W2963091658","https://openalex.org/W2963912046","https://openalex.org/W3026997957","https://openalex.org/W3034556525","https://openalex.org/W3034987089","https://openalex.org/W3098495697","https://openalex.org/W3102018700","https://openalex.org/W3174993810","https://openalex.org/W3212618200","https://openalex.org/W4221143046","https://openalex.org/W4280586943","https://openalex.org/W4281759695","https://openalex.org/W4362515116","https://openalex.org/W4366198844","https://openalex.org/W4382618722","https://openalex.org/W4385573588","https://openalex.org/W4386566859","https://openalex.org/W4389518605","https://openalex.org/W4389524486","https://openalex.org/W6765292183","https://openalex.org/W6809646742","https://openalex.org/W6838860814","https://openalex.org/W6851775633","https://openalex.org/W6852178287","https://openalex.org/W6854084413"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W3204019825","https://openalex.org/W4200363804","https://openalex.org/W2105693220","https://openalex.org/W2119476919"],"abstract_inverted_index":{"Logical":[0],"table-to-text":[1],"generation":[2,67,87],"(LT2T)":[3],"aims":[4],"to":[5,27,32,52,79],"generate":[6,115],"logically":[7,117],"faithful":[8,118],"textual":[9],"descriptions":[10,21],"from":[11,57],"tables.":[12],"However,":[13],"existing":[14],"end-to-end":[15],"LT2T":[16],"models,":[17],"which":[18],"directly":[19],"utilize":[20],"as":[22],"learning":[23],"objectives,":[24],"often":[25],"struggle":[26],"ensure":[28],"logical":[29,98,101],"faithfulness":[30],"due":[31],"the":[33,54,62,66,107,111,123,140],"absence":[34],"of":[35,68,125,131],"a":[36,49,73,85],"formal":[37],"reasoning":[38,46,55,63,81,92,99,112],"process.":[39],"To":[40],"solve":[41],"this":[42],"problem,":[43],"we":[44],"introduce":[45],"knowledge":[47,56,64,82,93,113],"transfer,":[48],"framework":[50,71,104],"designed":[51],"transfer":[53,74,80],"external":[58,77],"dataset":[59,78],"and":[60,83,100,114,135],"integrate":[61],"into":[65],"descriptions.":[69,119],"Our":[70,103],"fine-tunes":[72],"model":[75,88],"on":[76],"trains":[84],"knowledge-driven":[86],"by":[89],"using":[90],"transferred":[91],"with":[94,110],"two":[95],"self-supervised":[96],"objectives:":[97],"summary.":[102],"can":[105],"align":[106],"table":[108],"description":[109],"more":[116],"Experimental":[120],"results":[121],"show":[122],"effectiveness":[124],"our":[126],"method,":[127],"demonstrating":[128],"significant":[129],"improvements":[130],"1.9":[132],"in":[133,137],"SP-Acc":[134],"1.2":[136],"NLI-Acc":[138],"over":[139],"current":[141],"state-of-the-art":[142],"model.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}