{"id":"https://openalex.org/W4394726121","doi":"https://doi.org/10.3390/e26040325","title":"Enhancing Zero-Shot Stance Detection with Contrastive and Prompt Learning","display_name":"Enhancing Zero-Shot Stance Detection with Contrastive and Prompt Learning","publication_year":2024,"publication_date":"2024-04-11","ids":{"openalex":"https://openalex.org/W4394726121","doi":"https://doi.org/10.3390/e26040325","pmid":"https://pubmed.ncbi.nlm.nih.gov/38667879"},"language":"en","primary_location":{"id":"doi:10.3390/e26040325","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26040325","pdf_url":"https://www.mdpi.com/1099-4300/26/4/325/pdf?version=1712823707","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/26/4/325/pdf?version=1712823707","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102647349","display_name":"Zhenyin Yao","orcid":null},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyin Yao","raw_affiliation_strings":["School of Computer Science and Technology, Xinjiang University, Urumqi 830046, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xinjiang University, Urumqi 830046, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103199081","display_name":"Wudao Yang","orcid":"https://orcid.org/0009-0008-8604-0578"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenzhong Yang","raw_affiliation_strings":["School of Computer Science and Technology, Xinjiang University, Urumqi 830046, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xinjiang University, Urumqi 830046, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035603167","display_name":"Fuyuan Wei","orcid":"https://orcid.org/0009-0006-9660-3157"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuyuan Wei","raw_affiliation_strings":["School of Computer Science and Technology, Xinjiang University, Urumqi 830046, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xinjiang University, Urumqi 830046, China","institution_ids":["https://openalex.org/I96908189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103199081"],"corresponding_institution_ids":["https://openalex.org/I96908189"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":3.3689,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.92913728,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"26","issue":"4","first_page":"325","last_page":"325"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9955999851226807,"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":0.9955999851226807,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9891999959945679,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.987500011920929,"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":0.7874428033828735},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6818537712097168},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6573315858840942},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5869929790496826},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5854122638702393},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5744173526763916},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.571958065032959},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5501754879951477},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5408378839492798},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4960962235927582},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4905053973197937},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.24787059426307678}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7874428033828735},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6818537712097168},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6573315858840942},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5869929790496826},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5854122638702393},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5744173526763916},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.571958065032959},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5501754879951477},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5408378839492798},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4960962235927582},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4905053973197937},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.24787059426307678},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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":4,"locations":[{"id":"doi:10.3390/e26040325","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26040325","pdf_url":"https://www.mdpi.com/1099-4300/26/4/325/pdf?version=1712823707","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:38667879","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38667879","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11049083","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11049083","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11049083/pdf/entropy-26-00325.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:cb05011e8b054790bfa0ff976e253dc4","is_oa":true,"landing_page_url":"https://doaj.org/article/cb05011e8b054790bfa0ff976e253dc4","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 26, Iss 4, p 325 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/e26040325","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26040325","pdf_url":"https://www.mdpi.com/1099-4300/26/4/325/pdf?version=1712823707","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G427793495","display_name":null,"funder_award_id":"2020A02","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5577918188","display_name":null,"funder_award_id":"62262065","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5939423041","display_name":null,"funder_award_id":"Technology","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7608752429","display_name":null,"funder_award_id":"Talent","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"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/W4394726121.pdf"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W2150850338","https://openalex.org/W2437771934","https://openalex.org/W2460159515","https://openalex.org/W2519887557","https://openalex.org/W2741386817","https://openalex.org/W2767329425","https://openalex.org/W2799140283","https://openalex.org/W2896457183","https://openalex.org/W2984902757","https://openalex.org/W3002104146","https://openalex.org/W3023183123","https://openalex.org/W3035413677","https://openalex.org/W3044438666","https://openalex.org/W3091998006","https://openalex.org/W3096331697","https://openalex.org/W3096565276","https://openalex.org/W3119438769","https://openalex.org/W3126960149","https://openalex.org/W3154430186","https://openalex.org/W3161430799","https://openalex.org/W3175542874","https://openalex.org/W3176456866","https://openalex.org/W3185341429","https://openalex.org/W3198571508","https://openalex.org/W4224311791","https://openalex.org/W4224916560","https://openalex.org/W4285144860","https://openalex.org/W4285247752","https://openalex.org/W4321012240","https://openalex.org/W4321472119","https://openalex.org/W4385570657","https://openalex.org/W4387838552","https://openalex.org/W4389520082","https://openalex.org/W4391019401","https://openalex.org/W6778883912","https://openalex.org/W6796417832","https://openalex.org/W6798057236"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2378211422","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W2065370636"],"abstract_inverted_index":{"In":[0],"social":[1],"networks,":[2],"the":[3,10,30,40,95,107,119,125,160,178,181,188,197,207,217,232,236],"occurrence":[4],"of":[5,16,22,32,42,168,180,191],"unexpected":[6],"events":[7],"rapidly":[8],"catalyzes":[9],"widespread":[11],"dissemination":[12],"and":[13,100,113,130,146,219],"further":[14],"evolution":[15],"network":[17],"public":[18],"opinion.":[19],"The":[20],"advent":[21],"zero-shot":[23,155],"stance":[24,33,63,136,156],"detection":[25,34,137,157],"aligns":[26],"more":[27,210],"closely":[28],"with":[29,55,171,209],"characteristics":[31],"in":[35,70,77],"today's":[36],"digital":[37],"age,":[38],"where":[39],"absence":[41],"training":[43,66],"examples":[44],"for":[45,118,154],"specific":[46,128],"models":[47,54],"poses":[48],"significant":[49],"challenges.":[50],"This":[51,115],"task":[52],"necessitates":[53],"robust":[56],"generalization":[57],"abilities":[58],"to":[59,104,122,164,176,205],"discern":[60],"target-related,":[61],"transferable":[62],"features":[64,167],"within":[65],"data.":[67],"Recent":[68],"advances":[69],"prompt-based":[71],"learning":[72,110,149,204],"have":[73],"showcased":[74],"notable":[75],"efficacy":[76],"few-shot":[78],"text":[79],"classification.":[80],"Such":[81],"methods":[82],"typically":[83],"employ":[84],"a":[85,135,141,147,172,228],"uniform":[86],"prompt":[87,148,184],"pattern":[88],"across":[89],"all":[90],"instances,":[91,101,169],"yet":[92],"they":[93],"overlook":[94],"intricate":[96],"relationship":[97],"between":[98,127],"prompts":[99],"thereby":[102,194],"failing":[103],"sufficiently":[105],"direct":[106],"model":[108,138,208,234],"towards":[109],"task-relevant":[111],"knowledge":[112],"information.":[114],"paper":[116],"argues":[117],"critical":[120],"need":[121],"dynamically":[123,195],"enhance":[124],"relevance":[126],"instances":[129],"prompts.":[131],"Thus,":[132],"we":[133,201],"introduce":[134],"underpinned":[139],"by":[140],"gated":[142],"multilayer":[143],"perceptron":[144],"(gMLP)":[145],"strategy,":[150],"which":[151],"is":[152,162],"tailored":[153],"scenarios.":[158],"Specifically,":[159],"gMLP":[161],"utilized":[163],"capture":[165],"semantic":[166,189],"coupled":[170],"control":[173],"gate":[174,182],"mechanism":[175],"modulate":[177],"influence":[179],"on":[183,187,216,235],"tokens":[185],"based":[186],"context":[190],"each":[192],"instance,":[193],"reinforcing":[196],"instance-prompt":[198],"connection.":[199],"Moreover,":[200],"integrate":[202],"contrastive":[203],"empower":[206],"discriminative":[211],"feature":[212],"representations.":[213],"Experimental":[214],"evaluations":[215],"VAST":[218,237],"SEM16":[220],"benchmark":[221],"datasets":[222],"substantiate":[223],"our":[224],"method's":[225],"effectiveness,":[226],"yielding":[227],"1.3%":[229],"improvement":[230],"over":[231],"JointCL":[233],"dataset.":[238]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}