{"id":"https://openalex.org/W2970645034","doi":"https://doi.org/10.18653/v1/w19-5040","title":"PANLP at MEDIQA 2019: Pre-trained Language Models, Transfer Learning and Knowledge Distillation","display_name":"PANLP at MEDIQA 2019: Pre-trained Language Models, Transfer Learning and Knowledge Distillation","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2970645034","doi":"https://doi.org/10.18653/v1/w19-5040","mag":"2970645034"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w19-5040","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5040","pdf_url":"https://www.aclweb.org/anthology/W19-5040.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th BioNLP Workshop and Shared Task","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W19-5040.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100339289","display_name":"Wei Zhu","orcid":"https://orcid.org/0000-0002-6389-6866"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wei Zhu","raw_affiliation_strings":["Pingan Health Tech, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Pingan Health Tech, Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023696818","display_name":"Xiaofeng Zhou","orcid":"https://orcid.org/0000-0001-9837-1261"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaofeng Zhou","raw_affiliation_strings":["Pingan Health Tech, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Pingan Health Tech, Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101554486","display_name":"Keqiang Wang","orcid":"https://orcid.org/0000-0002-5322-365X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Keqiang Wang","raw_affiliation_strings":["Pingan Health Tech, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Pingan Health Tech, Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067068244","display_name":"Xun Luo","orcid":"https://orcid.org/0000-0002-1318-9418"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xun Luo","raw_affiliation_strings":["Pingan Health Tech, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Pingan Health Tech, Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019823426","display_name":"Xiepeng Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiepeng Li","raw_affiliation_strings":["Pingan Health Tech, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Pingan Health Tech, Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112109363","display_name":"Yuan Ni","orcid":"https://orcid.org/0009-0007-5406-7103"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan Ni","raw_affiliation_strings":["Pingan Health Tech, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Pingan Health Tech, Shanghai, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023775139","display_name":"Guotong Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guotong Xie","raw_affiliation_strings":["Pingan Health Tech, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Pingan Health Tech, Shanghai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100339289"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0804,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.93426223,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"380","last_page":"388"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9883999824523926,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9646999835968018,"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":0.8360425233840942},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6803074479103088},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6800103783607483},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6118882894515991},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6076894998550415},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5719547867774963},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.543993353843689},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5364587306976318},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.506827175617218},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5033900141716003},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.48311710357666016},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.469229519367218},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4672679007053375},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.45720013976097107},{"id":"https://openalex.org/keywords/knowledge-transfer","display_name":"Knowledge transfer","score":0.4116651117801666},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.061429738998413086},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.05795750021934509}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8360425233840942},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6803074479103088},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6800103783607483},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6118882894515991},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6076894998550415},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5719547867774963},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.543993353843689},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5364587306976318},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.506827175617218},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5033900141716003},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.48311710357666016},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.469229519367218},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4672679007053375},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.45720013976097107},{"id":"https://openalex.org/C2776960227","wikidata":"https://www.wikidata.org/wiki/Q2586354","display_name":"Knowledge transfer","level":2,"score":0.4116651117801666},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.061429738998413086},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.05795750021934509},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/w19-5040","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5040","pdf_url":"https://www.aclweb.org/anthology/W19-5040.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th BioNLP Workshop and Shared Task","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/w19-5040","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5040","pdf_url":"https://www.aclweb.org/anthology/W19-5040.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th BioNLP Workshop and Shared Task","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8299999833106995}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2970645034.pdf","grobid_xml":"https://content.openalex.org/works/W2970645034.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W1840435438","https://openalex.org/W2136189984","https://openalex.org/W2250539671","https://openalex.org/W2265846598","https://openalex.org/W2413794162","https://openalex.org/W2608787653","https://openalex.org/W2767989436","https://openalex.org/W2769041395","https://openalex.org/W2888120268","https://openalex.org/W2895604144","https://openalex.org/W2896457183","https://openalex.org/W2905933322","https://openalex.org/W2911489562","https://openalex.org/W2922551710","https://openalex.org/W2937297214","https://openalex.org/W2952650870","https://openalex.org/W2963341956","https://openalex.org/W2963769536","https://openalex.org/W2963854351","https://openalex.org/W2970986790","https://openalex.org/W4235216760","https://openalex.org/W4303684868"],"related_works":["https://openalex.org/W3201126466","https://openalex.org/W4282827391","https://openalex.org/W2169518243","https://openalex.org/W4386828785","https://openalex.org/W3165580226","https://openalex.org/W3034338377","https://openalex.org/W4385398839","https://openalex.org/W4384700341","https://openalex.org/W4394759804","https://openalex.org/W2791025012"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"the":[3,7,13,20,58,62,75,89,115,136,147,151,155,159,164,168],"models":[4,28,47,96,139],"designated":[5],"for":[6,123,150,158,167],"MEDIQA":[8],"2019":[9],"shared":[10],"tasks":[11,144],"by":[12,114],"team":[14],"PANLP.":[15],"We":[16,42],"take":[17],"advantages":[18],"of":[19,77,95,117,120],"recent":[21],"advances":[22],"in":[23,73,92,141],"pre-trained":[24,45],"bidirectional":[25],"transformer":[26],"language":[27,46],"such":[29],"as":[30],"BERT":[31],"(Devlin":[32],"et":[33,39],"al.,":[34,40],"2018)":[35],"and":[36,97,128,145,154,162],"MT-DNN":[37,79],"(Liu":[38],"2019b).":[41],"find":[43],"that":[44,112,118],"can":[48],"significantly":[49],"outperform":[50],"traditional":[51],"deep":[52],"learning":[53,56],"models.":[54,121],"Transfer":[55],"from":[57],"NLI":[59,160],"task":[60,64],"to":[61,70,87,108,134],"RQE":[63,152],"is":[65,85],"also":[66,163],"experimented,":[67],"which":[68],"proves":[69],"be":[71,109],"useful":[72],"improving":[74],"results":[76],"fine-tuning":[78],"large.":[80],"A":[81],"knowledge":[82,90],"distillation":[83],"process":[84,131],"implemented,":[86],"distill":[88],"contained":[91],"a":[93,129],"set":[94,119],"transfer":[98],"it":[99],"into":[100],"an":[101],"single":[102],"model,":[103],"whose":[104],"performance":[105],"turns":[106],"out":[107],"comparable":[110],"with":[111],"obtained":[113],"ensemble":[116,127],"Finally,":[122],"test":[124],"submissions,":[125],"model":[126],"re-ranking":[130],"are":[132],"implemented":[133],"boost":[135],"performances.":[137],"Our":[138],"participated":[140],"all":[142],"three":[143],"ranked":[146],"1st":[148],"place":[149,157,166],"task,":[153,161],"2nd":[156,165],"QA":[169],"task.":[170]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}