{"id":"https://openalex.org/W4412889958","doi":"https://doi.org/10.18653/v1/2025.acl-long.1221","title":"Document-Level Event-Argument Data Augmentation for Challenging Role Types","display_name":"Document-Level Event-Argument Data Augmentation for Challenging Role Types","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412889958","doi":"https://doi.org/10.18653/v1/2025.acl-long.1221"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.acl-long.1221","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1221","pdf_url":"https://aclanthology.org/2025.acl-long.1221.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 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.acl-long.1221.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086918380","display_name":"Joseph Gatto","orcid":"https://orcid.org/0000-0001-7013-2445"},"institutions":[{"id":"https://openalex.org/I107672454","display_name":"Dartmouth College","ror":"https://ror.org/049s0rh22","country_code":"US","type":"education","lineage":["https://openalex.org/I107672454"]},{"id":"https://openalex.org/I4210166639","display_name":"Dartmouth Hospital","ror":"https://ror.org/02j3qj605","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I4210166639"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Joseph Gatto","raw_affiliation_strings":["Department of Computer Science , Dartmouth College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , Dartmouth College","institution_ids":["https://openalex.org/I4210166639","https://openalex.org/I107672454"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021361292","display_name":"Omar Sharif","orcid":"https://orcid.org/0000-0002-1971-6522"},"institutions":[{"id":"https://openalex.org/I107672454","display_name":"Dartmouth College","ror":"https://ror.org/049s0rh22","country_code":"US","type":"education","lineage":["https://openalex.org/I107672454"]},{"id":"https://openalex.org/I4210166639","display_name":"Dartmouth Hospital","ror":"https://ror.org/02j3qj605","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I4210166639"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Omar Sharif","raw_affiliation_strings":["Department of Computer Science , Dartmouth College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , Dartmouth College","institution_ids":["https://openalex.org/I4210166639","https://openalex.org/I107672454"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035716941","display_name":"Parker Seegmiller","orcid":"https://orcid.org/0000-0001-6783-9773"},"institutions":[{"id":"https://openalex.org/I107672454","display_name":"Dartmouth College","ror":"https://ror.org/049s0rh22","country_code":"US","type":"education","lineage":["https://openalex.org/I107672454"]},{"id":"https://openalex.org/I4210166639","display_name":"Dartmouth Hospital","ror":"https://ror.org/02j3qj605","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I4210166639"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Parker Seegmiller","raw_affiliation_strings":["Department of Computer Science , Dartmouth College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , Dartmouth College","institution_ids":["https://openalex.org/I4210166639","https://openalex.org/I107672454"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066969862","display_name":"Sarah Masud Preum","orcid":"https://orcid.org/0000-0002-7771-8323"},"institutions":[{"id":"https://openalex.org/I107672454","display_name":"Dartmouth College","ror":"https://ror.org/049s0rh22","country_code":"US","type":"education","lineage":["https://openalex.org/I107672454"]},{"id":"https://openalex.org/I4210166639","display_name":"Dartmouth Hospital","ror":"https://ror.org/02j3qj605","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I4210166639"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Sarah Masud Preum","raw_affiliation_strings":["Department of Computer Science , Dartmouth College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , Dartmouth College","institution_ids":["https://openalex.org/I4210166639","https://openalex.org/I107672454"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.5175,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.93078724,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"25109","last_page":"25131"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9577000141143799,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9577000141143799,"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/T10028","display_name":"Topic Modeling","score":0.9448999762535095,"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/T10679","display_name":"Service-Oriented Architecture and Web Services","score":0.9408000111579895,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/argument","display_name":"Argument (complex analysis)","score":0.7111390829086304},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6948406100273132},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5649356842041016},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33918070793151855},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.33317071199417114}],"concepts":[{"id":"https://openalex.org/C98184364","wikidata":"https://www.wikidata.org/wiki/Q1780131","display_name":"Argument (complex analysis)","level":2,"score":0.7111390829086304},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6948406100273132},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5649356842041016},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33918070793151855},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33317071199417114},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.acl-long.1221","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1221","pdf_url":"https://aclanthology.org/2025.acl-long.1221.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 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.acl-long.1221","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1221","pdf_url":"https://aclanthology.org/2025.acl-long.1221.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 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3435271984","display_name":null,"funder_award_id":"DGE-2125733","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5704529688","display_name":null,"funder_award_id":"2125733","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337368","display_name":"Division of Graduate Education","ror":"https://ror.org/00whkrf32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412889958.pdf","grobid_xml":"https://content.openalex.org/works/W4412889958.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W3008380943","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2115206405","https://openalex.org/W2376932109"],"abstract_inverted_index":{"Event":[0],"Argument":[1],"Extraction":[2],"(EAE)":[3],"is":[4,23],"a":[5,33,106],"daunting":[6],"information":[7],"extraction":[8,115],"problem":[9],"-with":[10],"significant":[11,96],"limitations":[12],"in":[13,99,109,116],"few-shot":[14],"cross-domain":[15],"(FSCD)":[16],"settings.A":[17],"common":[18],"solution":[19],"to":[20,32,60],"FSCD":[21,117],"modeling":[22,41,51],"data":[24,63,72],"augmentation.Unfortunately,":[25],"existing":[26],"augmentation":[27,73],"methods":[28,74],"are":[29],"not":[30],"wellsuited":[31],"variety":[34],"of":[35,89],"real-world":[36],"EAE":[37,79],"contexts,":[38],"including":[39],"(i)":[40],"long":[42],"documents":[43],"(documents":[44],"with":[45,58],"over":[46],"10":[47],"sentences),":[48],"and":[49,64],"(ii)":[50],"challenging":[52],"role":[53,114],"types":[54],"(i.e.,":[55],"event":[56],"roles":[57],"little":[59],"no":[61],"training":[62,84],"semantically":[65],"outlying":[66],"roles).We":[67],"introduce":[68],"two":[69],"novel":[70],"LLMpowered":[71],"for":[75],"generating":[76],"extractive":[77],"document-level":[78],"samples":[80],"using":[81],"zero":[82],"in-domain":[83],"data.We":[85],"validate":[86],"the":[87],"generalizability":[88],"our":[90],"approach":[91],"on":[92,112],"four":[93],"datasets":[94],"-showing":[95],"performance":[97],"increases":[98],"low-resource":[100],"settings.Our":[101],"highest":[102],"performing":[103],"models":[104],"provide":[105],"13-pt":[107],"increase":[108],"F1":[110],"score":[111],"zero-shot":[113],"evaluation.":[118]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
