{"id":"https://openalex.org/W4287889132","doi":"https://doi.org/10.18653/v1/2022.semeval-1.153","title":"PALI at SemEval-2022 Task 7: Identifying Plausible Clarifications of Implicit and Underspecified Phrases in Instructional Texts","display_name":"PALI at SemEval-2022 Task 7: Identifying Plausible Clarifications of Implicit and Underspecified Phrases in Instructional Texts","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4287889132","doi":"https://doi.org/10.18653/v1/2022.semeval-1.153"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2022.semeval-1.153","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.semeval-1.153","pdf_url":"https://aclanthology.org/2022.semeval-1.153.pdf","source":{"id":"https://openalex.org/S4363608670","display_name":"Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)","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,"raw_source_name":"Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2022.semeval-1.153.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033057596","display_name":"Zhou Mengyuan","orcid":"https://orcid.org/0000-0002-7054-8800"},"institutions":[{"id":"https://openalex.org/I4210136318","display_name":"New York Life Insurance Company (United States)","ror":"https://ror.org/03a4nen96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210136318"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhou Mengyuan","raw_affiliation_strings":["An Life Insurance Company of China, Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"An Life Insurance Company of China, Ltd","institution_ids":["https://openalex.org/I4210136318"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063106324","display_name":"Dou Hu","orcid":"https://orcid.org/0000-0001-7790-8568"},"institutions":[{"id":"https://openalex.org/I4210136318","display_name":"New York Life Insurance Company (United States)","ror":"https://ror.org/03a4nen96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210136318"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dou Hu","raw_affiliation_strings":["An Life Insurance Company of China, Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"An Life Insurance Company of China, Ltd","institution_ids":["https://openalex.org/I4210136318"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102487705","display_name":"Mengfei Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136318","display_name":"New York Life Insurance Company (United States)","ror":"https://ror.org/03a4nen96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210136318"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mengfei Yuan","raw_affiliation_strings":["An Life Insurance Company of China, Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"An Life Insurance Company of China, Ltd","institution_ids":["https://openalex.org/I4210136318"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103661483","display_name":"Jin Zhi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136318","display_name":"New York Life Insurance Company (United States)","ror":"https://ror.org/03a4nen96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210136318"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jin Zhi","raw_affiliation_strings":["An Life Insurance Company of China, Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"An Life Insurance Company of China, Ltd","institution_ids":["https://openalex.org/I4210136318"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053576004","display_name":"Xiyang Du","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136318","display_name":"New York Life Insurance Company (United States)","ror":"https://ror.org/03a4nen96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210136318"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiyang Du","raw_affiliation_strings":["An Life Insurance Company of China, Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"An Life Insurance Company of China, Ltd","institution_ids":["https://openalex.org/I4210136318"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072836745","display_name":"Lianxin Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136318","display_name":"New York Life Insurance Company (United States)","ror":"https://ror.org/03a4nen96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210136318"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lianxin Jiang","raw_affiliation_strings":["An Life Insurance Company of China, Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"An Life Insurance Company of China, Ltd","institution_ids":["https://openalex.org/I4210136318"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418300","display_name":"Yang Mo","orcid":"https://orcid.org/0000-0001-6734-8691"},"institutions":[{"id":"https://openalex.org/I4210136318","display_name":"New York Life Insurance Company (United States)","ror":"https://ror.org/03a4nen96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210136318"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Mo","raw_affiliation_strings":["An Life Insurance Company of China, Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"An Life Insurance Company of China, Ltd","institution_ids":["https://openalex.org/I4210136318"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109423549","display_name":"Xiaofeng Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136318","display_name":"New York Life Insurance Company (United States)","ror":"https://ror.org/03a4nen96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210136318"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaofeng Shi","raw_affiliation_strings":["An Life Insurance Company of China, Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"An Life Insurance Company of China, Ltd","institution_ids":["https://openalex.org/I4210136318"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210136318"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07742891,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1084","last_page":"1089"},"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/T13629","display_name":"Text Readability and Simplification","score":0.9976000189781189,"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":0.8721886873245239},{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.8241209983825684},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.7268624305725098},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6608481407165527},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.6565918326377869},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6408441662788391},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5308899283409119},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4327716827392578}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8721886873245239},{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.8241209983825684},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.7268624305725098},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6608481407165527},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.6565918326377869},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6408441662788391},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5308899283409119},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4327716827392578},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2022.semeval-1.153","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.semeval-1.153","pdf_url":"https://aclanthology.org/2022.semeval-1.153.pdf","source":{"id":"https://openalex.org/S4363608670","display_name":"Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)","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,"raw_source_name":"Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2022.semeval-1.153","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.semeval-1.153","pdf_url":"https://aclanthology.org/2022.semeval-1.153.pdf","source":{"id":"https://openalex.org/S4363608670","display_name":"Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)","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,"raw_source_name":"Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8100000023841858,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4287889132.pdf","grobid_xml":"https://content.openalex.org/works/W4287889132.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W1572283139","https://openalex.org/W2640408555","https://openalex.org/W2785717964","https://openalex.org/W2896457183","https://openalex.org/W2963015836","https://openalex.org/W2965373594","https://openalex.org/W3005680577","https://openalex.org/W3035390927","https://openalex.org/W3048018176","https://openalex.org/W3056787299","https://openalex.org/W3122890974","https://openalex.org/W3126074026","https://openalex.org/W4287889455"],"related_works":["https://openalex.org/W1988325893","https://openalex.org/W4401042251","https://openalex.org/W4399511049","https://openalex.org/W4401042926","https://openalex.org/W2751613946","https://openalex.org/W4401042641","https://openalex.org/W4287887314","https://openalex.org/W2026429670","https://openalex.org/W4287888941","https://openalex.org/W4221151255"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"our":[3,133],"system":[4,36,47,134,184],"used":[5],"in":[6],"the":[7,39,53,63,119,138,147,176,179,195,210],"SemEval-2022":[8],"Task":[9],"7(Roth":[10],"et":[11],"al.):":[12],"Identifying":[13],"Plausible":[14],"Clarifications":[15],"of":[16,65,83,132,141,178,189,204],"Implicit":[17],"and":[18,69,90,111,155,197],"Underspecified":[19],"Phrases.Semeval":[20],"Task7":[21],"is":[22],"an":[23,81,112,152],"more":[24],"complex":[25],"cloze":[26,31],"task,":[27,32],"different":[28,84,108,142,166,180],"than":[29],"normal":[30],"only":[33,49],"requiring":[34],"NLP":[35,46],"could":[37],"find":[38],"best":[40,54],"fillers":[41,55,68],"for":[42,56],"sentence.In":[43],"Semeval":[44],"Task7,":[45],"not":[48],"need":[50],"to":[51,76,170],"choose":[52],"each":[57],"input":[58,114],"instance,":[59],"but":[60],"also":[61],"evaluate":[62],"quality":[64],"all":[66],"possible":[67],"give":[70],"them":[71],"a":[72,186,198],"relative":[73],"score":[74],"according":[75],"context":[77],"semantic":[78],"information.We":[79],"propose":[80],"ensemble":[82],"state-of-the-art":[85],"transformer-based":[86,143],"language":[87,124,162],"models(i.e.,":[88],"RoBERTa":[89],"Deberta)":[91],"with":[92],"some":[93],"plug-and-play":[94],"tricks,":[95],"such":[96],"as":[97],"Grouped":[98],"Layerwise":[99],"Learning":[100],"Rate":[101],"Decay":[102],"(GLLRD)":[103],"strategy,":[104],"contrastive":[105],"learning":[106,168],"loss,":[107],"pooling":[109,181],"head":[110,182],"external":[113],"data":[115],"preprecess":[116],"block":[117],"before":[118],"information":[120],"came":[121],"into":[122],"pretrained":[123,161],"models,":[125],"which":[126],"improve":[127,171],"performance":[128,139],"significantly.The":[129],"main":[130],"contributions":[131],"are":[135],"1)":[136],"revealing":[137],"discrepancy":[140],"pretraining":[144],"models":[145],"on":[146,191,194,206,209],"downstream":[148],"task;":[149],"2)":[150],"presenting":[151],"efficient":[153],"learning-rate":[154],"parameter":[156],"attenuation":[157],"strategy":[158],"when":[159],"fintuning":[160],"models;":[163],"3)":[164],"adding":[165],"constrative":[167],"loss":[169],"model":[172],"performance;":[173],"4)":[174],"showing":[175],"useful":[177],"structure.Our":[183],"achieves":[185],"test":[187,199],"accuracy":[188],"0.654":[190],"subtask1(ranking":[192],"4th":[193],"leaderboard)":[196],"Spearman's":[200],"rank":[201],"correlation":[202],"coefficient":[203],"0.785":[205],"subtask2(ranking":[207],"2nd":[208],"leaderboard).":[211]},"counts_by_year":[],"updated_date":"2026-09-08T07:41:39.490200","created_date":"2025-10-10T00:00:00"}