{"id":"https://openalex.org/W7211337286","doi":"https://doi.org/10.48550/arxiv.2609.06731","title":"Event Interaction in Low-Rank Bottlenecks for Temporal Relation Extraction","display_name":"Event Interaction in Low-Rank Bottlenecks for Temporal Relation Extraction","publication_year":2026,"publication_date":"2026-09-06","ids":{"openalex":"https://openalex.org/W7211337286","doi":"https://doi.org/10.48550/arxiv.2609.06731"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2609.06731","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.06731","pdf_url":"https://arxiv.org/pdf/2609.06731","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2609.06731","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5148480058","display_name":"Wei Sun","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Sun, Wei","raw_affiliation_strings":["Department of Computer Science , KU Leuven Celestijnenlaan 200A 3001 Heverlee , Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , KU Leuven Celestijnenlaan 200A 3001 Heverlee , Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137090957","display_name":"Tingyu Qu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Qu, Tingyu","raw_affiliation_strings":["Department of Computer Science , KU Leuven Celestijnenlaan 200A 3001 Heverlee , Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , KU Leuven Celestijnenlaan 200A 3001 Heverlee , Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126955775","display_name":"Jesse Davis","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Davis, Jesse","raw_affiliation_strings":["Department of Computer Science , KU Leuven Celestijnenlaan 200A 3001 Heverlee , Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , KU Leuven Celestijnenlaan 200A 3001 Heverlee , Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075796989","display_name":"Marie\u2010Francine Moens","orcid":"https://orcid.org/0000-0002-3732-9323","observed_orcids":["https://orcid.org/0000-0002-3732-9323"]},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Moens, Marie-Francine","raw_affiliation_strings":["Department of Computer Science , KU Leuven Celestijnenlaan 200A 3001 Heverlee , Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , KU Leuven Celestijnenlaan 200A 3001 Heverlee , Belgium","institution_ids":["https://openalex.org/I99464096"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99464096"],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9063000082969666,"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":0.9063000082969666,"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":0.07069999724626541,"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":0.0066999997943639755,"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/temporal-relation-extraction","display_name":"temporal relation extraction","score":1.0},{"id":"https://openalex.org/keywords/parameter-efficient-fine-tuning","display_name":"parameter-efficient fine-tuning","score":0.9850000143051147},{"id":"https://openalex.org/keywords/lora","display_name":"LoRa","score":0.7509999871253967},{"id":"https://openalex.org/keywords/adapters","display_name":"adapters","score":0.37400001287460327},{"id":"https://openalex.org/keywords/depthwise-convolution","display_name":"depthwise convolution","score":0.9369999766349792}],"concepts":[{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6071000099182129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5921000242233276},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5583000183105469},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45820000767707825},{"id":"https://openalex.org/C2987896495","wikidata":"https://www.wikidata.org/wiki/Q5416716","display_name":"Event data","level":3,"score":0.39500001072883606},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3549000024795532},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.3334999978542328},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27799999713897705},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:2609.06731","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.06731","pdf_url":"https://arxiv.org/pdf/2609.06731","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:lirias2repo.kuleuven.be:20.500.12942/792550","doi":null,"is_oa":false,"landing_page_url":"https://lirias.kuleuven.be/handle/20.500.12942/792550","pdf_url":null,"source":{"id":"https://openalex.org/S7407055369","display_name":"Lirias","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Transactions of the Association for Computational Linguistics (TACL)","raw_type":"info:eu-repo/semantics/article"},{"id":"doi:10.48550/arxiv.2609.06731","doi":"https://doi.org/10.48550/arxiv.2609.06731","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.06731","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.06731","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.06731","pdf_url":"https://arxiv.org/pdf/2609.06731","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G1410716723","display_name":"Interventions against polarisation in society for TRUSTworthy social media: from diagnosis to therapy (iTRUST).","funder_award_id":"G0L0822N","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"}],"funders":[{"id":"https://openalex.org/F4320319128","display_name":"Vlaams Supercomputer Centrum","ror":"https://ror.org/05sqppn31"},{"id":"https://openalex.org/F4320321730","display_name":"Fonds Wetenschappelijk Onderzoek","ror":"https://ror.org/03qtxy027"},{"id":"https://openalex.org/F4320327336","display_name":"Vlaamse regering","ror":null},{"id":"https://openalex.org/F4320338463","display_name":"CHIST-ERA","ror":"https://ror.org/00rbzpz17"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7211337286.pdf","grobid_xml":"https://content.openalex.org/works/W7211337286.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Temporal":[0],"relation":[1,146],"extraction":[2],"determines":[3],"whether":[4],"an":[5],"event":[6,32,91],"occurs":[7],"before,":[8],"after,":[9],"or":[10,34],"simultaneously":[11],"with":[12],"another":[13],"event,":[14],"and":[15,56,93,109,116,122],"therefore":[16],"relies":[17],"on":[18],"accurately":[19],"modeling":[20],"how":[21],"the":[22,104,114],"two":[23],"events":[24],"interact.":[25],"Mainstream":[26],"systems":[27],"achieve":[28],"this":[29,71],"by":[30],"concatenating":[31],"spans":[33],"using":[35],"shallow":[36],"fusion,":[37],"which":[38,83],"works":[39],"well":[40],"when":[41],"all":[42],"model":[43],"parameters":[44],"are":[45],"trainable.":[46],"However,":[47],"in":[48,113],"parameter-efficient":[49],"fine-tuning,":[50],"low-rank":[51,140],"bottlenecks":[52],"restrict":[53],"information":[54],"flow":[55],"prevent":[57],"these":[58],"interaction":[59,138],"signals":[60],"from":[61],"passing":[62],"through,":[63],"leading":[64],"to":[65,89,98,126],"clear":[66],"performance":[67],"drops.":[68],"To":[69],"address":[70],"limitation,":[72],"we":[73],"propose":[74],"a":[75],"theoretically":[76],"grounded":[77],"architecture,":[78],"Convolutional":[79],"Bottleneck":[80],"Interaction":[81],"(CBI),":[82],"first":[84],"applies":[85],"lightweight":[86],"depthwise":[87],"convolution":[88],"enhance":[90],"representations":[92],"then":[94],"uses":[95],"element-wise":[96],"multiplication":[97],"capture":[99],"effective":[100],"event-event":[101],"interactions":[102],"inside":[103,139],"bottleneck.":[105],"Across":[106],"five":[107],"datasets":[108],"seven":[110],"backbone":[111],"models":[112],"Adapter":[115],"LoRA":[117],"settings,":[118],"CBI":[119],"provides":[120],"consistent":[121],"substantial":[123],"gains,":[124],"up":[125],"+31.7":[127],"micro":[128],"F1,":[129],"while":[130],"adding":[131],"minimal":[132],"computational":[133],"cost,":[134],"showing":[135],"that":[136],"explicit":[137],"spaces":[141],"is":[142,150],"crucial":[143],"for":[144],"temporal":[145],"extraction.":[147],"The":[148],"code":[149],"available":[151],"at":[152],"https://github.com/VRCMF/CIF.git.":[153]},"counts_by_year":[],"updated_date":"2026-09-30T09:27:27.532063","created_date":"2026-09-07T00:00:00"}
