{"id":"https://openalex.org/W4416035207","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.142","title":"Improving Prompt Generalization for Cross-prompt Essay Trait Scoring from the Scoring-invariance Perspective","display_name":"Improving Prompt Generalization for Cross-prompt Essay Trait Scoring from the Scoring-invariance Perspective","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416035207","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.142"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.142","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.142","pdf_url":"https://aclanthology.org/2025.findings-emnlp.142.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-emnlp.142.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100677842","display_name":"Jiong Wang","orcid":"https://orcid.org/0000-0002-4632-6191"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiong Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100723814","display_name":"Shengquan Yu","orcid":"https://orcid.org/0000-0001-6110-6413"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shengquan Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2633","last_page":"2646"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.20579999685287476,"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":0.20579999685287476,"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":0.15129999816417694,"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/T12031","display_name":"Speech and dialogue systems","score":0.044199999421834946,"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/perspective","display_name":"Perspective (graphical)","score":0.7303000092506409},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5609999895095825},{"id":"https://openalex.org/keywords/trait","display_name":"Trait","score":0.45660001039505005},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.4406000077724457}],"concepts":[{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.7303000092506409},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5609999895095825},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.4593999981880188},{"id":"https://openalex.org/C106934330","wikidata":"https://www.wikidata.org/wiki/Q1971873","display_name":"Trait","level":2,"score":0.45660001039505005},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.4406000077724457},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43290001153945923},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39149999618530273},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.364300012588501},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.3118000030517578},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.29280000925064087},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.266400009393692}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-emnlp.142","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.142","pdf_url":"https://aclanthology.org/2025.findings-emnlp.142.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.142","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.142","pdf_url":"https://aclanthology.org/2025.findings-emnlp.142.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2369050462","display_name":null,"funder_award_id":"2022YFC3303600","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416035207.pdf","grobid_xml":"https://content.openalex.org/works/W4416035207.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Cross-prompt":[0],"trait":[1,25,94,109],"scoring":[2,8,15,27,79,104,111,125,145],"task":[3],"aims":[4],"to":[5,62,86,113,117],"learn":[6],"generalizable":[7],"capabilities":[9],"from":[10,45],"sourceprompt":[11],"data,":[12],"enabling":[13],"automatic":[14],"across":[16,88,127],"multiple":[17,89],"dimensions":[18],"on":[19,23,30,49,64,99],"unseen":[20],"essays.Existing":[21],"research":[22,43],"cross-prompt":[24],"essay":[26,69,132],"primarily":[28],"focuses":[29],"improving":[31],"model":[32,61,116],"generalization":[33],"by":[34],"obtaining":[35],"prompt-invariant":[36],"representations.In":[37],"this":[38],"paper,":[39],"we":[40,91],"approach":[41],"the":[42,60,68,83,103,115,119,136],"problem":[44],"a":[46,54,93,108],"different":[47],"perspective":[48],"invariance":[50],"learning":[51,56,77,130],"and":[52,106,147],"propose":[53,107],"scoring-invariant":[55],"objective.This":[57],"objective":[58,112],"encourages":[59],"focus":[63],"intrinsic":[65],"information":[66],"within":[67],"that":[70],"reflects":[71],"its":[72],"quality":[73],"during":[74],"training,":[75],"thereby":[76],"generic":[78],"features.To":[80],"further":[81],"enhance":[82],"model's":[84],"ability":[85],"score":[87],"dimensions,":[90],"introduce":[92],"feature":[95],"extraction":[96],"network":[97],"based":[98],"routing":[100],"gates":[101],"into":[102],"architecture":[105],"consistency":[110,126],"encourage":[114],"balance":[118],"diversity":[120],"of":[121,138],"trait-specific":[122,131],"features":[123],"with":[124,151],"traits":[128],"when":[129],"features.Extensive":[133],"experiments":[134],"demonstrate":[135],"effectiveness":[137],"our":[139],"approach,":[140],"showing":[141],"advantages":[142],"in":[143],"multi-trait":[144],"performance":[146],"achieving":[148],"significant":[149],"improvements":[150],"lowresource":[152],"prompts.":[153]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-08T00:00:00"}
