{"id":"https://openalex.org/W7138385642","doi":"https://doi.org/10.1609/aaai.v40i15.38224","title":"PromptEmo: Learning Emotion with Bilateral Textual Prompts in Multi-Domain Open-set Scenarios","display_name":"PromptEmo: Learning Emotion with Bilateral Textual Prompts in Multi-Domain Open-set Scenarios","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138385642","doi":"https://doi.org/10.1609/aaai.v40i15.38224"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i15.38224","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i15.38224","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i15.38224","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049361630","display_name":"Xinyi Zeng","orcid":"https://orcid.org/0000-0003-4625-5474"},"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":true,"raw_author_name":"Xinyi Zeng","raw_affiliation_strings":["Sichuan University"],"affiliations":[{"raw_affiliation_string":"Sichuan University","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129641996","display_name":"Yuxiang Yang","orcid":null},"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":"Yuxiang Yang","raw_affiliation_strings":["Sichuan University"],"affiliations":[{"raw_affiliation_string":"Sichuan University","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006002666","display_name":"Pinxian Zeng","orcid":"https://orcid.org/0000-0001-7286-974X"},"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":"Pinxian Zeng","raw_affiliation_strings":["Sichuan University"],"affiliations":[{"raw_affiliation_string":"Sichuan University","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129670854","display_name":"Wenxia Yin","orcid":null},"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":"Wenxia Yin","raw_affiliation_strings":["Sichuan University"],"affiliations":[{"raw_affiliation_string":"Sichuan University","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129731098","display_name":"Bo Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Bo Liu","raw_affiliation_strings":["The Hong Kong Polytechnic University"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129674897","display_name":"Xi Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I24201400","display_name":"Chengdu University of Information Technology","ror":"https://ror.org/01yxwrh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I24201400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Wu","raw_affiliation_strings":["Chengdu University of Information Technology"],"affiliations":[{"raw_affiliation_string":"Chengdu University of Information Technology","institution_ids":["https://openalex.org/I24201400"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129654870","display_name":"Yan O. Wang","orcid":null},"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":"Yan Wang","raw_affiliation_strings":["Sichuan University"],"affiliations":[{"raw_affiliation_string":"Sichuan University","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5049361630"],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.575,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"15","first_page":"12322","last_page":"12330"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9745000004768372,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9745000004768372,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.004900000058114529,"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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.003800000064074993,"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/discriminative-model","display_name":"Discriminative model","score":0.7541999816894531},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7182000279426575},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.6299999952316284},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5546000003814697},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5504999756813049},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5103999972343445},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4921000003814697},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4745999872684479}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7541999816894531},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7182000279426575},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6966000199317932},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.6299999952316284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6097000241279602},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5546000003814697},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5504999756813049},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5404999852180481},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5103999972343445},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4921000003814697},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4745999872684479},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.453000009059906},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.38089999556541443},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.3393999934196472},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3142000138759613},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3050000071525574},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.27709999680519104},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2685000002384186},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C6438553","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Affective computing","level":2,"score":0.2556000053882599}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i15.38224","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i15.38224","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i15.38224","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i15.38224","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7401337623596191,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Facial":[0],"Expression":[1],"Recognition":[2],"(FER)":[3],"is":[4],"crucial":[5],"to":[6,27,44,51,58,71,100,131,171],"human-computer":[7],"interaction.":[8],"Existing":[9],"cross-domain":[10],"FER":[11,83,227],"(CD-FER)":[12],"methods":[13],"mainly":[14],"focus":[15],"on":[16,189,222],"single-source":[17],"closed-set":[18],"scenarios,":[19],"transferring":[20],"knowledge":[21],"from":[22,47,146],"a":[23,28,72,91,141,208,231],"single":[24],"source":[25],"domain":[26,30],"target":[29,61],"with":[31,118],"identical":[32],"class":[33,65],"sets.":[34],"However,":[35],"CD-FER":[36],"faces":[37],"two":[38,147],"real-world":[39],"challenges:":[40],"1)":[41],"the":[42,56,105,109,133,167,180,215,235],"need":[43],"leverage":[45],"information":[46],"multiple":[48],"sources,":[49],"leading":[50],"multi-domain":[52],"shift,":[53],"and":[54,74,151,159,178],"2)":[55],"necessity":[57],"recognize":[59],"unseen":[60,136,223],"classes,":[62,124],"resulting":[63,196],"in":[64,104,197],"shift.":[66],"These":[67],"issues":[68],"give":[69],"rise":[70],"novel":[73,92],"challenging":[75],"task,":[76],"which":[77],"we":[78,88,139],"define":[79],"as":[80,125,127,230],"Multi-domain":[81],"Open-set":[82],"(MO-FER).":[84],"In":[85],"this":[86],"paper,":[87],"propose":[89],"PromptEmo,":[90],"CLIP-based":[93,168],"framework":[94],"that":[95,202],"leverages":[96],"bilateral":[97,176],"textual":[98,149,169],"prompts":[99,117,130,177],"address":[101],"both":[102],"shifts":[103],"MO-FER":[106,236],"task.":[107,237],"Leveraging":[108],"generalizability":[110],"of":[111],"LLM,":[112],"PromptEmo":[113,213],"constructs":[114],"trainable":[115],"positive":[116],"LLM-generated":[119],"emotion":[120,204],"descriptions":[121],"for":[122,135,234],"seen":[123],"well":[126],"template-derived":[128],"negative":[129],"enhance":[132],"reasoning":[134],"classes.":[137],"Then,":[138],"introduce":[140],"modal-task":[142],"optimization":[143],"paradigm":[144],"organized":[145],"perspectives:":[148],"semantics":[150],"visual":[152,182],"domains,":[153],"yielding":[154],"Intra-modal":[155],"Space-specific":[156],"Optimization":[157],"(ISO)":[158],"Cross-modal":[160],"Emotion-aware":[161],"Interaction":[162],"(CEI)":[163],"strategies.":[164],"ISO":[165],"refines":[166],"space":[170,183],"ensure":[172],"semantic":[173],"separation":[174],"between":[175],"improves":[179],"latent":[181],"by":[184,206,219],"promoting":[185],"inter-domain":[186],"alignment.":[187],"Founded":[188],"ISO,":[190],"CEI":[191],"facilitates":[192],"effective":[193],"vision-language":[194],"interactions,":[195],"four":[198,226],"joint":[199],"loss":[200],"terms":[201],"improve":[203],"recognition":[205],"shaping":[207],"domain-invariant,":[209],"discriminative":[210],"feature":[211],"space.":[212],"surpasses":[214],"current":[216],"SOTA":[217],"method":[218],"7.7%":[220],"AUC":[221],"classes":[224],"across":[225],"datasets,":[228],"serving":[229],"strong":[232],"baseline":[233]},"counts_by_year":[],"updated_date":"2026-03-20T20:47:17.329874","created_date":"2026-03-18T00:00:00"}