{"id":"https://openalex.org/W4412888899","doi":"https://doi.org/10.18653/v1/2025.findings-acl.43","title":"Evaluating Instructively Generated Statement by Large Language Models for Directional Event Causality Identification","display_name":"Evaluating Instructively Generated Statement by Large Language Models for Directional Event Causality Identification","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412888899","doi":"https://doi.org/10.18653/v1/2025.findings-acl.43"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.43","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.43","pdf_url":"https://aclanthology.org/2025.findings-acl.43.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: ACL 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-acl.43.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Wei Xiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Xiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112963475","display_name":"Chuanhong Zhan","orcid":"https://orcid.org/0000-0002-7466-3494"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chuanhong Zhan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100358770","display_name":"Qing Zhang","orcid":"https://orcid.org/0000-0001-5312-2800"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qing Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Bang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bang Wang","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":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"779","last_page":"785"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9722999930381775,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9722999930381775,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9452999830245972,"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":0.9333000183105469,"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":0.7132595777511597},{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.651793897151947},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6478809118270874},{"id":"https://openalex.org/keywords/statement","display_name":"Statement (logic)","score":0.6315780878067017},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5479585528373718},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4768482446670532},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3349001705646515},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.28320837020874023},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07980242371559143},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.07442611455917358}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7132595777511597},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.651793897151947},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6478809118270874},{"id":"https://openalex.org/C2777026412","wikidata":"https://www.wikidata.org/wiki/Q2684591","display_name":"Statement (logic)","level":2,"score":0.6315780878067017},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5479585528373718},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4768482446670532},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3349001705646515},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.28320837020874023},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07980242371559143},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.07442611455917358},{"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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.43","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.43","pdf_url":"https://aclanthology.org/2025.findings-acl.43.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: ACL 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-acl.43","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.43","pdf_url":"https://aclanthology.org/2025.findings-acl.43.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: ACL 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G5824610820","display_name":null,"funder_award_id":"62172167","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"},{"id":"https://openalex.org/F4320322186","display_name":"Natural Science Foundation of Hubei Province","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412888899.pdf","grobid_xml":"https://content.openalex.org/works/W4412888899.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W167088980","https://openalex.org/W2475705533","https://openalex.org/W186129870","https://openalex.org/W3200522959","https://openalex.org/W4389944781","https://openalex.org/W2997993211","https://openalex.org/W120415280","https://openalex.org/W4383099232","https://openalex.org/W1993275793","https://openalex.org/W2753931199"],"abstract_inverted_index":{"This":[0],"paper":[1],"aims":[2],"to":[3,23,86,90,113,126,144],"identify":[4,95,114],"directional":[5,66,96],"causal":[6,26,55],"relations":[7],"between":[8],"events,":[9],"including":[10],"the":[11,40,50,58,70,101,116,138,141,146,154],"existence":[12,38,117,147],"and":[13,49,94,109,118,148,156],"direction":[14,119,149],"of":[15,52,73,120,140,150],"causality.Previous":[16],"studies":[17],"mainly":[18],"adopt":[19],"prompt":[20],"learning":[21],"paradigm":[22],"predict":[24],"a":[25,31,88,124],"answer":[27,44,60],"word":[28,61],"based":[29,131],"on":[30,132,153],"Pretrained":[32],"Language":[33,76],"Model":[34],"(PLM)":[35],"for":[36],"causality":[37,67,92,98,129],"identification.However,":[39],"indecision":[41],"in":[42,65,79],"selecting":[43],"words":[45],"from":[46],"some":[47],"synonyms":[48],"confusion":[51],"indicating":[53],"opposite":[54],"directions":[56],"with":[57,168],"same":[59],"raise":[62],"more":[63],"challenges":[64],"identification.Inspired":[68],"by":[69,99],"strong":[71],"capabilities":[72],"pre-trained":[74],"Generative":[75],"Models":[77],"(GLMs)":[78],"generating":[80],"responses":[81],"or":[82],"statements,":[83],"we":[84,104,136],"propose":[85,105],"instruct":[87],"GLM":[89,125],"generate":[91,128],"statements":[93,130,143],"event":[97,133,151],"evaluating":[100],"generated":[102,142],"statements.Specifically,":[103],"an":[106],"Instructive":[107],"Generation":[108],"Statement":[110],"Evaluation":[111],"method":[112,162],"both":[115],"causality.We":[121],"first":[122],"fine-tune":[123],"instructively":[127],"description":[134],"inputs.Then,":[135],"evaluate":[137],"rationality":[139],"determine":[145],"causalities.Experiments":[152],"ESC":[155],"MAVEN":[157],"datasets":[158],"show":[159],"that":[160],"our":[161],"significantly":[163],"outperforms":[164],"state-of-the-art":[165],"algorithms,":[166],"even":[167],"fewer":[169],"training":[170],"data.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
