{"id":"https://openalex.org/W4396759407","doi":"https://doi.org/10.1145/3589334.3645318","title":"LFDe: A Lighter, Faster and More Data-Efficient Pre-training Framework for Event Extraction","display_name":"LFDe: A Lighter, Faster and More Data-Efficient Pre-training Framework for Event Extraction","publication_year":2024,"publication_date":"2024-05-08","ids":{"openalex":"https://openalex.org/W4396759407","doi":"https://doi.org/10.1145/3589334.3645318"},"language":"en","primary_location":{"id":"doi:10.1145/3589334.3645318","doi":"https://doi.org/10.1145/3589334.3645318","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589334.3645318","pdf_url":null,"source":{"id":"https://openalex.org/S7407088480","display_name":"International World Wide Web Conference (WWW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033504019","display_name":"Zhigang Kan","orcid":"https://orcid.org/0000-0002-8929-1961","observed_orcids":["https://orcid.org/0000-0002-8929-1961"]},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigang Kan","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-8929-1961","affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082986901","display_name":"Liwen Peng","orcid":"https://orcid.org/0000-0003-1202-9583","observed_orcids":["https://orcid.org/0000-0003-1202-9583"]},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liwen Peng","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-1202-9583","affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011016539","display_name":"Yifu Gao","orcid":"https://orcid.org/0000-0002-1743-8055","observed_orcids":["https://orcid.org/0000-0002-1743-8055"]},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifu Gao","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-1743-8055","affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100432409","display_name":"Ning Liu","orcid":"https://orcid.org/0000-0002-8966-7869","observed_orcids":["https://orcid.org/0000-0002-8966-7869"]},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Liu","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-8966-7869","affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043045076","display_name":"Linbo Qiao","orcid":"https://orcid.org/0000-0002-8285-2738","observed_orcids":["https://orcid.org/0000-0002-8285-2738"]},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linbo Qiao","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-8285-2738","affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100440903","display_name":"Dongsheng Li","orcid":"https://orcid.org/0000-0001-9743-2034","observed_orcids":["https://orcid.org/0000-0001-9743-2034"]},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongsheng Li","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-9743-2034","affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":1.1549,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.78246144,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3964","last_page":"3975"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9872999787330627,"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":0.9872999787330627,"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":0.0071000000461936,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.0008999999845400453,"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/event-extraction","display_name":"event extraction","score":0.9950000047683716},{"id":"https://openalex.org/keywords/pretraining","display_name":"pre-training","score":0.8790000081062317},{"id":"https://openalex.org/keywords/pseudo-events","display_name":"pseudo-events","score":0.7179999947547913},{"id":"https://openalex.org/keywords/data-efficiency","display_name":"data efficiency","score":0.5690000057220459},{"id":"https://openalex.org/keywords/memory-efficient-training","display_name":"memory-efficient training","score":0.6610000133514404},{"id":"https://openalex.org/keywords/data-scarce-scenarios","display_name":"data-scarce scenarios","score":0.8569999933242798}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8318375945091248},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6060531735420227},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6031904220581055},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5549842119216919},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5381119847297668},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4670644700527191},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.45621079206466675},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4437030553817749},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.44260168075561523},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.44233864545822144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43416890501976013},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589334.3645318","doi":"https://doi.org/10.1145/3589334.3645318","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589334.3645318","pdf_url":null,"source":{"id":"https://openalex.org/S7407088480","display_name":"International World Wide Web Conference (WWW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W2081580037","https://openalex.org/W2094728533","https://openalex.org/W2250575108","https://openalex.org/W2250999640","https://openalex.org/W2251628379","https://openalex.org/W2475245295","https://openalex.org/W2512522169","https://openalex.org/W2618285232","https://openalex.org/W2788525741","https://openalex.org/W2914431807","https://openalex.org/W2952437275","https://openalex.org/W2972140869","https://openalex.org/W2981852735","https://openalex.org/W2982399380","https://openalex.org/W3035229828","https://openalex.org/W3102925419","https://openalex.org/W3103519070","https://openalex.org/W3104597568","https://openalex.org/W3104890489","https://openalex.org/W3129626847","https://openalex.org/W3137968039","https://openalex.org/W3170759063","https://openalex.org/W3174870841","https://openalex.org/W3174945605","https://openalex.org/W3176032431","https://openalex.org/W3177112239","https://openalex.org/W3177413495","https://openalex.org/W4221159406","https://openalex.org/W4221166835","https://openalex.org/W4225938243","https://openalex.org/W4285276432","https://openalex.org/W4287019595","https://openalex.org/W4287887850","https://openalex.org/W4377235148","https://openalex.org/W4385567149","https://openalex.org/W4385570528","https://openalex.org/W4385571102","https://openalex.org/W4385572128","https://openalex.org/W4386424393"],"related_works":["https://openalex.org/W3167383427","https://openalex.org/W3199510093","https://openalex.org/W4306670470","https://openalex.org/W4281630710","https://openalex.org/W4385571102","https://openalex.org/W4367308305","https://openalex.org/W3106625509","https://openalex.org/W4318614875","https://openalex.org/W4412445503","https://openalex.org/W4396240313"],"abstract_inverted_index":{"Pre-training":[0],"Event":[1],"Extraction":[2],"(EE)":[3],"models":[4],"on":[5,74,112,164],"unlabeled":[6],"data":[7,19,94,178],"is":[8],"an":[9],"effective":[10],"strategy":[11],"that":[12,61,168],"frees":[13],"researchers":[14],"from":[15,58,81],"costly":[16],"and":[17,33,48,97,109,127,188],"labor-intensive":[18],"annotation.":[20],"However,":[21],"existing":[22,59],"pre-training":[23,51,120,126,177,184],"methods":[24,60],"necessitate":[25],"substantial":[26],"computational":[27],"resources,":[28],"requiring":[29],"high-performance":[30],"hardware":[31],"infrastructure":[32],"extensive":[34],"training":[35],"duration.":[36],"In":[37,122],"response":[38],"to":[39,63,118,140,159,170],"these":[40],"challenges,":[41],"this":[42,161],"paper":[43,148],"proposes":[44],"a":[45,65,82,151,182],"Lighter,":[46],"Faster,":[47],"more":[49],"Data-efficient":[50],"framework":[52,72,130,174,196],"for":[53,157],"EE,":[54],"named":[55],"LFDe.":[56],"Distinct":[57],"strive":[62],"establish":[64],"comprehensive":[66],"representation":[67],"space":[68],"during":[69,100],"pre-training,":[70,96],"our":[71,173,195],"focuses":[73],"quickly":[75],"familiarizing":[76],"with":[77],"the":[78,101,113,123,129,134,141,144],"task":[79],"format":[80],"small":[83],"amount":[84],"of":[85,115,125,136],"automatically":[86,106],"constructed":[87],"pseudo-events.":[88],"It":[89],"comprises":[90],"three":[91],"stages:":[92],"weak-label":[93],"construction,":[95],"fine-tuning.":[98],"Specifically,":[99],"first":[102,105],"stage,":[103],"LFDe":[104],"designates":[107],"pseudo-triggers":[108],"arguments":[110],"based":[111],"characteristics":[114],"real":[116],"events":[117],"form":[119],"samples.":[121],"processes":[124],"fine-tuning,":[128],"reframes":[131],"EE":[132,158],"as":[133],"identification":[135],"tokens":[137],"semantically":[138],"closest":[139],"prompt":[142],"within":[143],"given":[145],"sentence.":[146],"This":[147],"also":[149],"introduces":[150],"novel":[152],"prompt-based":[153],"sequence":[154],"labeling":[155],"model":[156],"accommodate":[160],"reframing.":[162],"Experiments":[163],"real-world":[165],"datasets":[166],"show":[167],"compared":[169],"similar":[171],"models,":[172],"requires":[175],"fewer":[176],"(only":[179],"about":[180],"0.04%),":[181],"shorter":[183],"period":[185],"(about":[186,192],"0.03%),":[187],"lower":[189],"memory":[190],"requirements":[191],"57.6%).":[193],"Simultaneously,":[194],"significantly":[197],"improves":[198],"performance":[199],"in":[200],"various":[201],"data-scarce":[202],"scenarios.":[203]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2}],"updated_date":"2026-10-26T11:51:55.731654","created_date":"2024-05-09T00:00:00"}
